- Published: 31 January 2014
A systematic review on cloud computing
- Frederico Durao 1 ,
- Jose Fernando S. Carvalho 2 ,
- Anderson Fonseka 2 &
- Vinicius Cardoso Garcia 2
The Journal of Supercomputing volume 68 , pages 1321–1346 ( 2014 ) Cite this article
5328 Accesses
106 Citations
Metrics details
Cloud computing is an ascending technology that has introduced a new paradigm by rendering a rational computational model possible. It has changed the dynamics of IT consumption by means of a model that provides on-demand services over the Internet. Unlike the traditional hosting service, cloud computing services are paid for per usage and may expand or shrink based on demand. Such services are, in general, fully managed by cloud providers that require users nothing but a personal computer and an Internet access. In recent years, this model has attracted the attention of researchers, investors and practitioners, many of whom have proposed a number of applications, structures and fundamentals of cloud computing, resulting in various definitions, requirements and models. Despite the interest and advances in the field, issues such as security and privacy, service layer agreement, resource sharing, and billing have opened up new questions about the real gains of the model. Although cloud computing is based on a 50-year-old business model, evidence from this study indicates that cloud computing still needs to expand and overcome present limitations that prevent the full use of its potential. In this study, we critically review the state of the art in cloud computing with the aim of identifying advances, gaps and new challenges.
This is a preview of subscription content, access via your institution .
Access options
Buy single article.
Instant access to the full article PDF.
Price excludes VAT (USA) Tax calculation will be finalised during checkout.
Rent this article via DeepDyve.
http://cabig.cancer.gov/ .
http://www.earthsystemgrid.org/home.htm .
http://searchcloudcomputing.techtarget.com/definition/cloud-computing .
http://www.sri.com/sites/default/files/brochures/dec-05.pdf .
http://www.gartner.com/newsroom/id/2537815/ .
http://www.networkworld.com/news/2013/073013/cloud-computing-disaster-recovery-272370.html .
http://assertlab.com/ .
Amazon (2012) Amazon web services. URL: http://aws.amazon.com/ . Retrieved 24 Oct 2013
Apple (1983) Apple invents the personal computer. URL: http://archive.computerhistory.org/resources/text/Apple/Apple.Lisa.1983.102634506.pdf . Retrieved 24 Oct 2013
Baliga J, Ayre RWA, Hinton K, Tucker RS (2010) Green cloud computing: balancing energy in processing, storage and transport. J Proc IEEE 99
Basili VR, Zelkowitz MV (2007) Empirical studies to build a science of computer science. Commun ACM 50(11):33–37
Article Google Scholar
Bellis M (1997) The history of computers. URL: http://inventors.about.com/library/blcoindex.htm . Retrieved 24 Oct 2013
Berners-Lee T (1998) The world wide web: a very short personal history
Boloor K, Chirkova R, Viniotis Y, Salo T (2010) Dynamic request allocation and scheduling for context aware applications subject to a percentile response time sla in a distributed cloud. In: IEEE International Conference and Workshops on Cloud Computing Technology and Science (CLOUDCOM’10)
Bonetta D, Pautasso C (2011) Towards liquid service oriented architectures. In: International conference on World Wide Web, Hyderabad, India
Budgen D, Kitchenham BA, Charters SM, Turner M, Brereton P, Linkman SG (2008) Presenting software engineering results using structured abstracts: a randomised experiment. Empirical Softw Eng 13(4):435–468
Buyya R, Yeo CS, Venugopal S, Broberg J, Brandic I (2009) Cloud computing and emerging it platforms: vision, hype, and reality for delivering computing as the 5th utility. Future Comput Syst 25(6):599–616
Cadan KS, Li WS, Phan T, Zhou M (2009) Frontiers in information and software as services. In: International Conference on Data, Engineering (ICDE’09)
Calero JMA, Edwards N, Kirschnick J, Wilcock L, Wray M (2010) Toward a multi-tenancy authorization system for cloud services. J Secur Priv 8:48–55
Campbell-Kelly M (2009) Historical reflections the rise, fall, and resurrection of software as a service. J CACM 52
Caron E, Desprez F, Muresan A (2011) Pattern matching based forecast of non-periodic repetitive behavior for cloud clients. J Grid Comput 9:49–64
Carr NG (2003) It doesn’t matter. In: Harvard Business School
Chapman C, Emmerich W, Márquez FG, Clayman S, Galis A (2011) Software architecture definition for on-demand cloud provisioning. J Cluster Comput 14:1–22
Chaves SA, Westphall CB, Lamin FR (2010) Sla perspective in security management for cloud computing. In: International Conference on Networking and Services (ICNS’10)
Chellappa RK (1997) Intermediaries in cloud-computing: A new computing paradigm. In INFORMS Annual Meeting, Dallas
Chieu T, Kapoor S, Mohindra A, Shaikh A (2010) Cross enterprise improvements delivered via a cloud platform: a game changer for the consumer product and retail industry. In: International Conference on Services, Computing (SCC’10)
Cho B, Gupta I (2010) New algorithms for planning bulk transfer via internet and shipping networks. In: International Conference on Distributed, Computing Systems (ICDCS’10)
Chong F, Carraro G (2006) Architecture strategies for catching the long tail. MSDN Library, Microsoft Corporation, pp 9–10
Columbus L (2011) Gartner releases their hype cycle for cloud computing, 2011. URL: http://goo.gl/pqrDC , 2011. Retrieved 24 Oct 2013
Costa R, Brasileiro F, Filho GL, Souza DM (2009) Oddci: on-demand distributed computing infrastructure. In: Workshop on Many-Task Computing on Grids and Supercomputers (MTAGS’09)
Doelitzscher F, Reich C, Sulistio A (2010) Designing cloud services adhering to government privacy laws. In: Complex, Intelligent and Software Intensive Systems (CIT’10)
Dutreilh X, Moreau A, Malenfant J, Rivierre N, Truck I (2010) Data center resource allocation to control theory and back. In: International Conference on Cloud, Computing (CLOUD’10)
Elmroth E, Larsson L (2009) Interfaces for placement, migration, and monitoring of virtual machines in federated clouds. In: International Conference on Grid and Cooperative, Computing (GCC’09)
Erl T (2005) Service-oriented architecture (SOA): concepts, technology, and design. Prentice Hall
Foster I (1998) The grid: blueprint for a new computing infrastructure. Morgan Kaufmann Publishers Inc, Burlington
Google Scholar
Gill K (2008) Remember the oil crisis? URL: http://uspolitics.about.com/b/2008/01/02/remember-the-oil-crisis.htm . Retrieved 24 Oct 2013
Guha R, Al-Dabass D (2010) Impact of web 2.0 and cloud computing platform on software engineering. In: Proceedings of the 2010 International Symposium on Electronic System Design (ISED’10), pp 213–218
Hassan MM, Song B, Huh EN (2009) A framework of sensor, cloud integration opportunities and challenges. In: International Conference on Ubiquitous Information Management and Communication (ICUIMC’09)
Hou Z, Zhou X (2010) Asaas: application software as a service for high performance cloud computing. In: International Conference on High Performance Computing and Communications (HPCC’10)
Huang H, Wang L (2010) P&p: a combined push-pull model for resource monitoring in cloud computing environment. In: International Conference on Cloud, Computing (CLOUD’10)
Hutchinson C, Ward J, Castilon K (2009) Navigating the application architecture. J IT Prof 11:18–22
Ichak A (1996) The pursuit of prime: maximize your company’s success with the Adizes Program. Knowledge Exchange
Jianhong Z, Hua C (2010) Secuirty storage in the cloud computing: a rsa-based assumption data integrity check without original data. In: International Conference on Educational and Information Technology (ICEIT’10)
Jin H, Xiang G, Zou D, Wu S, Zhao F, Li M, Zheng W (2011) A vmm-based intrusion prevention system in cloud computing environment. J Supercomput 66:1133–1151
Kandukuri BP, Paturi VR (2009) Cloud security issues. In: International Conference on Services, Computing (SCC’09)
Kansal A, Zhao F, Liu J, Kothari N, Bhattacharya AA (2010) Virtual machine power metering and provisioning. In: ACM symposium on Cloud computing (SoCC’10)
Kertész A, Kecskeméti G, Brandic I (2011) Autonomic sla-aware service virtualization for distributed systems. In: Euromicro Conference on Parallel, Distributed and Network-based (PDP’11)
Kitchenham B, Charters S (2007) Guidelines for performing systematic literature reviews in software engineering. Technical Report EBSE 2007–001, Keele University and Durham University Joint, Report
Kondo D, Javadi B, Malecot P, Cappello F, Anderson DP (2009) Cost-benefit analysis of cloud computing versus desktop grids. In: IEEE International Symposium on Parallel and Distributed Processing with Applications (IPDPS’09)
Kossmann D, Kraska T, Loesing S (2010) An avaluation of alternative architectures for transaction processing in the cloud. In: International conference on Management of data (SIGMOD’10)
Kozuch MA, Ryan MP, Gass R, Schlosser SW, O’Hallaron, Cipar J, Krevat E, ópez JL, Stroucken M, Ganger GR (2009) Tashi: location-aware cluster management. In: International Conference on AC and DC Power Transmission (ACDC’09)
Kumar SR, Saxena A (2011) Data integrity proofs in cloud storage. In: International Conference on COMmunication Systems and NETworkS (COMSNETS’11)
Kutare M, Eisenhauer G, Wang C, Schwan K, Talwar V, Wolf M (2010) Monalytics: Online monitoring and analytics for managing large scale data centers. In: International Conference on Autonomic Computing (ICAC’10), Washington
Lee JH, Park MW, Eom JH, Chung TM (2011) Multi-level intrusion detection system and log management in cloud computing. In: International Conference on Advanced Communication Technology (ICACT’11)
Li J, Zhao G, Chen X, Xie D, Rong C, Li W, Tang L, Tang Y (2010) Fine-grained data access control systems with user accountability in cloud computin. In: IEEE International Conference and Workshops on Cloud Computing Technology and Science (CLOUDCOM’10)
Li Q, Hao Q, Xiao L, Li Z (2009) Adaptive management of virtualized resources in cloud computing using feedback control. In: International Conference on Information Science and Engineering (ICISE’09)
Lin FT, Shih TS (2010) Cloud computing: the emerging computing technology. J ICIC Int 1:33–38
Luo M, Zhang LJ, Lei F (2010) An insuanrance model for guranteeing service assurance, integrity and qos in cloud computing. In: International Conference on Web Services (ICWS’10)
Macías M, Fitó JO, Guitart J (2010) Rule-based sla management for revenue maximisation in cloud computing markets. In: International Conference on network and Service Management (CNSM’10)
Madnick S (1969) Time-sharing systems: virtual machine conept vs. conventional approach. J Modern Data Sys 2:34–36
Marston S, Li Z, Bandyopadhyay S, Zhang J, Ghalsasi A (2010) Cloud computing-the business perspective. J Decis Support Syst 51:176–189
McCarthy J (1983) Reminiscences on the history of time-sharing. URL: http://www-formal.stanford.edu/jmc/history/timesharing.dvi , 1983. Retrieved 02 June 2012
Mehta HK, Kanungo P, Chandwani M (2011) Performance enhancement of scheduling algorithms in clusters and grids using improved dynamic load balancing techniques. In: International conference on World Wide Web (WWW’11)
Menzel M, Warschofsky R, Thomas I, Willems C, Meinel C (2010) The service security lab: A model-driven platform to compose and explore service security in the cloud. In: World Congress on Services (SERVICES-I’10)
Mounzer J, Bambos N (2010) Integrated security risk management for it-intensive organizations. In: International Conference on Information Assurance and Security (IAS’10)
Nae V, Prodan R, Losup A (2011) A new business model for massively multiplayer online games. In: International conference on Performance, engineering (ICPE’11)
Nair SK, Porwal S, Dimitrakos T, Ferrer AJ, Tordsson J, Sharif T, Sheridan C, Rajarajan M, Khan AU (2010) Towards secure cloud bursting, brokerage and aggregation. In: International Conference on Web Services
Nicolae B (2010) High throughput data-compression for cloud storage. Lect Notes Comput Sci 6265(2010):1–12
NITRD (1991) High performance computing act of 1991. URL: http://www.nitrd.gov/Congressional/Laws/pl_102-194.html , 1991. Retrieved 24 Oct 2013
Parkhill DF (1966) The challenge of the computer utility. Addison-Wesley Publishing Company, Boston
Pervez Z, Khattak AM, Lee S, Lee YK (2010) Dual validation framework for multi-tenant saas architecture. In: Future Information Technology (FutureTech’10)
Petersen K, Feldt R, Mujtaba S, Mattsson M (2008) Systematic mapping studies in software engineering. In: Evaluation and Assessment in Software Engineering (EASE’08), Italy. University of Bari
Polsson K (2012) Chronology of personal computers. URL: http://www.islandnet.com/kpolsson/comphist/comp1988.htm , 2012. Retrieved 24 Oct 2013
Ramakrishman L, Jackson KR, Canon S, Cholia S, Shalf J (2010) Defining future platform requirements for e-science clouds. In: ACM symposium on Cloud, computing (SoCC’10)
Rimal BR, Jukan A, Katsaros D, Goeleven Y (2010) Architectural requirements for cloud computing systems: an enterprise cloud approach. J Grid Comput 9:3–26
Per R, Martin H (2009) Guidelines for conducting and reporting case study research in software engineering. Empirical Softw Engg 14(2):131–164
Salesforce.com (2013) Salesforce.com. last checked oct/2013. URL: www.salesforce.com , 2013. Retrieved 24 Oct 2013
David S, Farheen A (2010) Taking a flexible approach to asps. J CACM 53:139–143
Sevior M, Fifield T, Katayama N (2010) Belle monte-carlo production on the amazon ec2 cloud. J Phys Conf Ser 219 012003. doi: 10.1088/1742-6596/219/1/012003
Shi A, Xia Y, Zhan H (2010) Applying cloud computing in financial service industry. In: International Conference on Intelligent Control and Information Processing (ICICIP’10)
Foster I, Zhao Y, Raicu L, Shiyong L (2008) Cloud computing and grid computing 360-degree compared. URL: http://arxiv.org/ftp/arxiv/papers/0901/0901.0131.pdf , 2008. Retrived 24 Oct 2013
Sigh MD, Krishna PR, Saxena A (2010) A cryptography based privacy preserving solution to mine cloud data. In: Proceedings of the Annual ACM Bangalore Conference (COMPUTE’10)
Sivathanu S, Liu L, Yiduo M, Pu X (2010) Storage management in virtualized cloud environment. In: International Conference on Cloud, Computing (CLOUD’10)
Smarr L (2008) Metacomputer architecture of the global lambdagrid: How personal light paths are transforming e-science. URL: http://goo.gl/ohpfMR , 2008. Retrieved 24 Oct 2013
Spring J (2011) Monitoring cloud computing by layer, part 1. J IEEE Secur Priv 9:66–68
Staten J (2009) Hollow out the moose: reducing cost with strategic rightsourcing. Forrester Research Inc, Cambridge
Tao Q, Chang H, Yi Y, Gu C (2010) A trustworthy management approach for cloud services qos data. In: International Conference on Machine Learning and Cybernetics (ICMLC’10)
Taylor M, Haggerty J, Gresty D, Hegarty R (2010) Digital evidence in cloud computing systems. J Comput Law Secur Rep Rev 26:204–208
Thelen E (2010) General electric computer department from the bottom up 1961 through 1965. URL: http://www.ed-thelen.org/EarlyGE-Computers.html , 2010. Retrieved 24 Oct 2013
Udo H (2010) Data protection and legal compliance in cloud computing. J DuD 34:554–556
Wang J, Varman P (2010) Avoiding performance fluctuation in cloud storage. In: International Conference on High, Performance Computing (HiPC’10)
Wang Y, Song A, Luo J (2010) A mapreducemerge-based data cube construction method. In: International Conference on Grid and Cooperative, Computing (GCC’10)
Wayne NIST, Jansen A (2011) Cloud hooks: security and privacy issues in cloud computing. In: Hawaii International Conference on System Sciences (HICSS’11)
Christof W, Arun A, Benjamin B, Nikolay B, Thomas M, Wibke M, Jochen S (2009) Cloud computing: a classification, business models, and research directions. J Bus Inform Syst Eng 1:391–399
Woitaszek M, Tufo HM (2010) Developing a cloud computing charging model for high-performance computing resources. In: CIT, IEEE Computer Society, pp 210–217
Wong WK, Cheung DW, Kao B, Mamoulis N (2009) Secure knn computation on encrypted databases. In: International conference on Management of data (SIGMOD’09)
Wu H, Winer C (2009) Network security for virtual machine in cloud computing? In: International Conference on Computer Sciences and Convergence Information Technology (ICCIT’09)
Yigitbasi N, Iosup A, Epema D, Ostermann S (2009) C-meter: a framework for performance analysis of computing clouds. In: IEEE/ACM International Symposium on Cluster, Cloud and Grid, Computing (CCGrid’09)
Yu X, Wen Q (2010) A view about cloud data security from data life cycle. In: International Conference on Computational Intelligence and Software Engineering (CiSE’10)
Yusuke T, Koie H, Tomohiro K, Isao K, Yoshio T (2010) A distributed storage system allowing application users to reserve i/o performance in advance for achieving sla. In: International Workshop on Middleware for Grids, Clouds and e-Science (MGC’10)
Zhang Q, Cheng L, Boutaba R (2010) Cloud computing: state-of-the-art and research challenges. J Internet Serv Appl 1(1):7–18
Zheng Q, Xu S (2010) Fail and dynamic proofs of retrievability. In: ACM Conference on Data and Application Security and Privacy (CODASPY’10)
Zhou M, Zhang R, Xie W, Qian W, Zhou A (2010) Security and privacy in cloud computing: a survey. In: International Conference on Semantics Knowledge and Grid (SKG’10)
Zhou W, Ning P, Wang R, Zhang X, Ammons G, Bala V (2010) Always up-to-date -slacalable offline patching of vm images in a compute cloud. In: Annual Computer Security Applications Conference (ACSAC’10)
Zissis D, Lekkas D (2011) Securing e-government and e-voting with an open cloud computing architecture. J Gov Inform Quart 28:239–251
Download references
Acknowledgments
The authors would like to thank the ASSERT Research Group for the feedback on meetings and support during the execution of this research. This work was partially supported by the National Institute of Science and Technology for Software Engineering (INES), funded by CNPq and FACEPE, grants 573964/2008-4 and APQ-1037-1.03/08.
Author information
Authors and affiliations.
Computer Science Department, Federal University of Bahia, Salvador, BA, Brazil
Frederico Durao
Informatic Center, Federal University of Pernambuco, Recife, PE, Brazil
Jose Fernando S. Carvalho, Anderson Fonseka & Vinicius Cardoso Garcia
You can also search for this author in PubMed Google Scholar
Corresponding author
Correspondence to Frederico Durao .
Rights and permissions
Reprints and Permissions
About this article
Cite this article.
Durao, F., Carvalho, J.F.S., Fonseka, A. et al. A systematic review on cloud computing. J Supercomput 68 , 1321–1346 (2014). https://doi.org/10.1007/s11227-014-1089-x
Download citation
Published : 31 January 2014
Issue Date : June 2014
DOI : https://doi.org/10.1007/s11227-014-1089-x
Share this article
Anyone you share the following link with will be able to read this content:
Sorry, a shareable link is not currently available for this article.
Provided by the Springer Nature SharedIt content-sharing initiative
- Cloud computing
- Service layer agreement
- Virtualization
- On-demand business model
Advertisement
Skip to Main Content
IEEE Account
- Change Username/Password
- Update Address
Purchase Details
- Payment Options
- Order History
- View Purchased Documents
Profile Information
- Communications Preferences
- Profession and Education
- Technical Interests
- US & Canada: +1 800 678 4333
- Worldwide: +1 732 981 0060
- Contact & Support
- About IEEE Xplore
- Accessibility
- Terms of Use
- Nondiscrimination Policy
- Privacy & Opting Out of Cookies
A not-for-profit organization, IEEE is the world's largest technical professional organization dedicated to advancing technology for the benefit of humanity. © Copyright 2023 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.
An official website of the United States government
The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.
The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.
- Publications
- Account settings
- My Bibliography
- Collections
- Citation manager
Save citation to file
Email citation, add to collections.
- Create a new collection
- Add to an existing collection
Add to My Bibliography
Your saved search, create a file for external citation management software, your rss feed.
- Search in PubMed
- Search in NLM Catalog
- Add to Search
A Systematic Review on Cloud Storage Mechanisms Concerning e-Healthcare Systems
Affiliations.
- 1 Research Institute of Network and Information Security, Shenzhen University, Shenzhen 518060, China.
- 2 College of Computer Science and Software Engineering, Shenzhen University, Shenzhen 518060, China.
- 3 Department of Accounting and Information System, College of Business and Economics, Qatar University, Doha P.O. Box. 2713, Qatar.
- 4 Department of Computer Science, City University of Science and Information Technology, Peshawar 25000, Pakistan.
- 5 Department of Computer Science, University of Swabi, Ambar 23430, Pakistan.
- 6 Cyberspace Institute of Technology, Guangzhou University, Guangzhou 510006, China.
- PMID: 32967094
- PMCID: PMC7570508
- DOI: 10.3390/s20185392
As the expenses of medical care administrations rise and medical services experts are becoming rare, it is up to medical services organizations and institutes to consider the implementation of medical Health Information Technology (HIT) innovation frameworks. HIT permits health associations to smooth out their considerable cycles and offer types of assistance in a more productive and financially savvy way. With the rise of Cloud Storage Computing (CSC), an enormous number of associations and undertakings have moved their healthcare data sources to distributed storage. As the information can be mentioned whenever universally, the accessibility of information becomes an urgent need. Nonetheless, outages in cloud storage essentially influence the accessibility level. Like the other basic variables of cloud storage (e.g., reliability quality, performance, security, and protection), availability also directly impacts the data in cloud storage for e-Healthcare systems. In this paper, we systematically review cloud storage mechanisms concerning the healthcare environment. Additionally, in this paper, the state-of-the-art cloud storage mechanisms are critically reviewed for e-Healthcare systems based on their characteristics. In short, this paper summarizes existing literature based on cloud storage and its impact on healthcare, and it likewise helps researchers, medical specialists, and organizations with a solid foundation for future studies in the healthcare environment.
Keywords: availability; cloud computing; cloud storage; deduplication; e-Healthcare; erasure coding; replication.
Conflict of interest statement
The authors declare no conflict of interest.
Strategic workflow of the paper’s…
Strategic workflow of the paper’s literature and analysis.
Basic factors of cloud storage.
Hierarchy of cloud storage availability…
Hierarchy of cloud storage availability and its mechanisms.
Erasure coding general workflow.
Erasure coding working example with…
Erasure coding working example with k = 4 , m = 2 ,…
Workflow of data deduplication.
Pie chart representation of distribution…
Pie chart representation of distribution of total discussed approaches based on primary and…
Similar articles
- eHealth Cloud Security Challenges: A Survey. Al-Issa Y, Ottom MA, Tamrawi A. Al-Issa Y, et al. J Healthc Eng. 2019 Sep 3;2019:7516035. doi: 10.1155/2019/7516035. eCollection 2019. J Healthc Eng. 2019. PMID: 31565209 Free PMC article. Review.
- Hybrid Approach for Improving the Performance of Data Reliability in Cloud Storage Management. Alzahrani A, Alyas T, Alissa K, Abbas Q, Alsaawy Y, Tabassum N. Alzahrani A, et al. Sensors (Basel). 2022 Aug 10;22(16):5966. doi: 10.3390/s22165966. Sensors (Basel). 2022. PMID: 36015727 Free PMC article.
- Government Cloud Computing Policies: Potential Opportunities for Advancing Military Biomedical Research. Lebeda FJ, Zalatoris JJ, Scheerer JB. Lebeda FJ, et al. Mil Med. 2018 Nov 1;183(11-12):e438-e447. doi: 10.1093/milmed/usx114. Mil Med. 2018. PMID: 29425378
- IFHDS: Intelligent Framework for Securing Healthcare BigData. Essa YM, Hemdan EE, El-Mahalawy A, Attiya G, El-Sayed A. Essa YM, et al. J Med Syst. 2019 Mar 27;43(5):124. doi: 10.1007/s10916-019-1250-4. J Med Syst. 2019. PMID: 30919123
- Behavioral Reference Model for Pervasive Healthcare Systems. Tahmasbi A, Adabi S, Rezaee A. Tahmasbi A, et al. J Med Syst. 2016 Dec;40(12):270. doi: 10.1007/s10916-016-0632-0. Epub 2016 Oct 14. J Med Syst. 2016. PMID: 27743241
- Energy saving strategy of cloud data computing based on convolutional neural network and policy gradient algorithm. Yang D, Yu J, Du X, He Z, Li P. Yang D, et al. PLoS One. 2022 Dec 30;17(12):e0279649. doi: 10.1371/journal.pone.0279649. eCollection 2022. PLoS One. 2022. PMID: 36584089 Free PMC article.
- Design of Cloud Storage-Oriented Sports Physical Fitness Monitoring System. Zheng Z, Liu Y. Zheng Z, et al. Comput Intell Neurosci. 2022 Jun 10;2022:1889381. doi: 10.1155/2022/1889381. eCollection 2022. Comput Intell Neurosci. 2022. PMID: 35720923 Free PMC article.
- Security challenges and solutions using healthcare cloud computing. Mehrtak M, SeyedAlinaghi S, MohsseniPour M, Noori T, Karimi A, Shamsabadi A, Heydari M, Barzegary A, Mirzapour P, Soleymanzadeh M, Vahedi F, Mehraeen E, Dadras O. Mehrtak M, et al. J Med Life. 2021 Jul-Aug;14(4):448-461. doi: 10.25122/jml-2021-0100. J Med Life. 2021. PMID: 34621367 Free PMC article. Review.
- Deep Learning Approach for Discovery of In Silico Drugs for Combating COVID-19. Jha N, Prashar D, Rashid M, Shafiq M, Khan R, Pruncu CI, Tabrez Siddiqui S, Saravana Kumar M. Jha N, et al. J Healthc Eng. 2021 Jul 20;2021:6668985. doi: 10.1155/2021/6668985. eCollection 2021. J Healthc Eng. 2021. PMID: 34326978 Free PMC article.
- Mell P.M., Grance T. The NIST definition of cloud computing. NIST. 2011 doi: 10.6028/NIST.SP.800-145. - DOI
- Sun D.W., Chang G.R., Gao S., Jin L.Z., Wang X.W. Modeling a Dynamic Data Replication Strategy to Increase System Availability in Cloud Computing Environments. J. Comput. Sci. Technol. 2012;27:256–272. doi: 10.1007/s11390-012-1221-4. - DOI
- Alami Milani B., Jafari Navimipour N. A comprehensive review of the data replication techniques in the cloud environments: Major trends and future directions. J. Netw. Comput. Appl. 2016;64:229–238. doi: 10.1016/j.jnca.2016.02.005. - DOI
- Wang X., Wang Y., Gao C., Lin K., Li Y. Automatic diagnosis with efficient medical case searching based on evolving graphs. IEEE Access. 2018;6:53307–53318. doi: 10.1109/ACCESS.2018.2871769. - DOI
- Kohli R., Tan S.S.L. Electronic health records: How can IS researchers contribute to transforming healthcare? MIS Q. 2016;40:553–573. doi: 10.25300/MISQ/2016/40.3.02. - DOI
Publication types
- Search in MeSH
LinkOut - more resources
Full text sources.
- Europe PubMed Central
- PubMed Central
- MedlinePlus Health Information
Research Materials
- NCI CPTC Antibody Characterization Program
- Citation Manager
NCBI Literature Resources
MeSH PMC Bookshelf Disclaimer
The PubMed wordmark and PubMed logo are registered trademarks of the U.S. Department of Health and Human Services (HHS). Unauthorized use of these marks is strictly prohibited.
- International Journal of Engineering Research & Technology (IJERT)
- Mission & Scope
- Editorial Board
- Peer-Review Policy
- Publication Ethics Policy
- Journal Policies
- Join as Reviewer
- Conference Partners
- Call for Papers
- Journal Statistics – 2021-2022
- Submit Manuscript
- Journal Charges (APC)
- Register as Volunteer
- Upcoming Conferences
- CONFERENCE PROCEEDINGS
- Thesis Archive
- Thesis Publication FAQs
- Thesis Publication Charges
- Author Login
- Reviewer Login
Volume 02, Issue 02 (February 2013)
A systematic review on cloud computing.
- Article Download / Views: 688
- Total Downloads : 370
- Authors : Balinder Singh
- Paper ID : IJERTV2IS2414
- Volume & Issue : Volume 02, Issue 02 (February 2013)
- Published (First Online): 28-02-2013
- ISSN (Online) : 2278-0181
- Publisher Name : IJERT
Balinder Singh
Probably in the 21st century, cloud computing is the most considerable new technique and hot researching area in IT world. It is now conveying huge impact to the society, mainly the business world. It provides services on demand basis over internet, which allows the clients to focus on their major chores without worrying about purchasing infrastructure and installing it to data processing. Many reputed IT companies, such as Amazon, Google, Microsoft, IBM,
Public Cloud
Hybrid Cloud
Private Cloud
Yahoo and so on, developed cloud computing system and provide services for a huge amount of users. However, it produces too facilities which can make peoples live easy, but we cannot decline the truth that it is near to public domain, resulting prone to security leakage. Due to security issues and challenges, costumers are slow in adopting it. In this paper, we performed a systematic review including the following terms: Evolution, definitions and characteristics of cloud computing, and then introduced its models (i.e. deployment model, service model), cloud vendors with their products, finally security issues and challenges
Software as a Service
Platform as a Service Infrastructure as a Service
Figure1. Cloud Computing Environment
related to cloud computing. In cloud computing environment it is an important issue to provide secure and reliable services. This paper can be very useful to anyone who have heard the word cloud computing for the first time and interested to know what it is.
1. Introduction
Over the past few years, progress in the field of computing and applications on demand over internet have led to an unstable growth of application models such as cloud computing, community network, software as a service, storage on web, and so on. In the era of the Internet, major application such as, Cloud Computing has become a considerable research topic of the industrial communities and scientific since 2007. Cloud computing represents a new era for delivery and utilization of the services over the Internet. Clouds are a large pool of easily usable and accessible virtualized resources (such as server, hard disk, database or development platform, and so on). For best resource utilization, these resources can be dynamically reconfigured to adjust to an unpredictable load.
Cloud Computing provides computer infrastructure and services "on-need" basis. The computing infrastructure could include server, hard disk, CPU cycles, database, development platform or complete software applications, and so on. Users (organizations and individuals) do not need to pay any large scale capital expenditures to access these resources from the cloud vendors. These users need to "pay-per-use" i.e. they need to pay only as much as they use the computing infrastructure. The billing model of cloud computing is pay-per-use such as the electricity or water payment that we do on the basis of usage. Thus it reduces hardware and software investment cost. In between 2008 and 2009, according to a survey undertaken by the International Data Corporation (IDC) group, the majority of results point to utilize Cloud computing as a low-cost feasible option to users [5]. Vender of cloud computing provides the services over the web, so these services are available from any location. The consumer does not need to know anything about the software, interface services, and platform. All the information can be abstracted from
consumers, and who has no control over these. In spite of the fact that cloud computing offers large opportunities to the IT industry, the improvement of cloud computing technology is currently at its infancy, there are many issues still to be addressed.
The rest of the paper is organized as follows. Section II introduces evaluation of Cloud. In section III we will introduce Cloud Computing overview; in section IV commercial product of cloud computing and security challenges will be discussed in final section V.
2. Evolution of the cloud
The evolution of Cloud computing shown in figure 2, passed through the following: networking, network sharing, information sharing, resources sharing, and services sharing [8]. The first stage of the Cloud was something like networking, having multiple regional networks with linked computers; initially it is adopted by national labs and universities. Then Connectivity among these regional networks with TCP/IP, led to Internet and its worldwide adoption. Using of HTML format and HTTP protocol, let to World Wide Web for exchange of information by using Mosaic browser. Then resource sharing came into picture with the emerging of grid computing. It provided standards and software for sharing of remote resources and collaboration; it was accepted for highly scalable High Performance Computing (HPC) jobs. The latest stage of the cloud, known as Cloud Computing, provides facilities of sharing the services over web by abstracting the infrastructure complexities of servers, heterogeneous platforms, computing power or complete software applications, and so on.
accepted by industries and academic world. Many researchers and research institutes have provided their own definitions. According to IDC [12]: An emerging IT development, deployment and delivery model, enabling real-time delivery of products, services and solutions over the Internet (i.e., enabling cloud services). There exist several definitions of cloud computing, among these a widespread definition is defined by the US National Institute of Standards and Technology (NIST) [13] as follows: "Cloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. This cloud model is composed of five essential characteristics, three service models, and four deployment models."
3.2. Cloud computing characteristics
Cloud computing has many characteristics by that it is going to be so popular. These are:
On-demand self-service: A consumer need not a human interaction with resources (such as CPU time, storage or software application and so on) providers to obtain these computing resources.
Shared resource pooling: In cloud computing, by the infrastructure provider, a pool of computing resources can be dynamically allocated to different consumers. In this sense, the consumers do not have knowledge or control over the exact location of these resources.
Virtualization: Needs and use of cloud computing services are not related to specific physical resources or exact location of those. Using virtualization, customer can access servers or storage without knowing details
Services Sharing
Resources Sharing
Information Network Sharing Networking
Cloud Computing Grid Computing World Wide Web
of specific server or storage. The virtualization layer in computing model executes consumer request for computing resources by accessing appropriate resources. Virtualization can help to improve server utilization.
High availability: Cloud computing platform deploys multiple copies of the data, computing nodes use exchangeable technology to protect the service availability. If during execution any computing nodes failure happens, the application running on that node will mov to other computing node to continue running, without the user's knowledge of the situation. Cloud computing provides higher availability than
Figure2. Evolution of cloud computing
3. Cloud computing overview
3.1. Definition
Cloud computing is still an evolving paradigm, definition and nuance of this have no universally
other computing models.
Rapid elasticity: For a consumer, there is no restriction on the usage of computing resources. These resources can be increased or decreased on need basis. It provides a platform of dynamically increase or
decrease IT resources according to application needs by customers every time and anywhere.
Utility-based pricing: It provides pay-per-use billing model that allows calculating the usage of clouds services by per client on regular bases. Users buy on demand, and pay like the electricity, water, gas supply.
Broad network access: Computing resources are available over network and also accessed by different heterogeneous platforms (such as laptop, desktop, mobile phone, PDA or tablet).
Multi-tenancy: In the environment of cloud, services possessed by multiple providers are co-located in a single data center. The management and performance issues related to these services are shared by these service providers and the infrastructure provider. Cloud computing layered architecture describes the responsibilities; only specific objectives related to each layer are focused by the owner of particular layer.
Geo-distribution and universal network access: A customer of Clouds can access the services of cloud every time and anywhere over the Internet through internet connectivity devices such as desktop, laptop, mobile phone, PDA or tablet.
Cost-effective: The main aim of cloud computing is to provide such an environment to the consumers of cloud to fulfill all their requirement without purchasing or upgrading the software and hardware (such as server, hard disk and so on) according to their needs. But they have to pay as per they use the cloud services and for the Maintenance of hardware at their own side. Thus this may lead to cost saving.
Cloud computing deployment model
Cloud computing is classified in four deployment models, but in figure 1, only three basic cloud computing deployment models have been depicted. These four are as follow:
Public Cloud: Cloud infrastructure is made available for public use or for a large industry group and is managed and operated by the public cloud service provider. This is a model which allows users to access the cloud through interfaces using web browsers. The user has no control and visibility over where the computing infrastructure is situated. The computing infrastructure is shared among any no. of Organizations. It is usually based on a pay-per-use billing model. Public cloud helps the cloud clients to reduce the operation costs on IT expenditure [3]. However, public clouds owns less security as compared to other cloud models because all the information on
the public cloud are more prone to malicious attacks due to its open structure.
Private Cloud: The cloud infrastructure is operated exclusively within a single organization. Similar to Intranet functionality, in private cloud all the cloud resources and applications are managed by the organization itself. Only the organization and its designated stakeholders may have authority to operate on a particular Private Cloud [10]. Thus it can achieve the most effective control over data, security, compliance and service quality under the control of the enterprises [17]. Private clouds are more secure and more costly compared to public clouds.
Hybrid cloud: a typical combination of private cloud and public cloud together forms a new model called hybrid cloud. in this model a private cloud is combined with one or more external (public) cloud services, centrally managed, as a single entity and bounded by a secure network [6]. that means the hybrid cloud can supply services for both the creator and their users. it enables the organizations to use private cloud for state-steady workload, and requesting the public cloud when peak workload occurs, then return if public cloud services no longer needed [19]. when consumers use hybrid cloud computing model for security purpose, they should use private cloud to run core applications and store internal sensitive data, but non-core applications can be executed on public cloud. in hybrid cloud, the service providers need to pay higher cost for deployment and have to face more complex security problems., community cloud: the cloud infrastructure is shared by many organizations of the same community, having similar interest and requirement, which may reduce utilization cost. the cloud infrastructure could be organized by one of the organizations in the community or by a third-party provider..
3.4. Cloud computing service model
There are three best known cloud computing service model (depicted in figure 1) described individually as follow:
Software as a Service (SaaS) consists of a complete software which is offered by cloud vendor on the cloud infrastructure. By using SaaS model, users can access these software applications on pay-per-use basis. Users do not need to purchase software products and install them on their own computer or server and run these applications on the users system [24]. In some cases these software products are free to use, but with limited right. These applications can be accessed remotely by
different devices (i.e. desktop, laptop, mobile phone, PDA or tablet) through a thin client interface such as a web browser. The consumer does not need to control or manage the underlying cloud infrastructure. Presently, the SaaS applications are online services such as e-mail services, Google Docs, Microsoft Office Live, online antivirus, web conference, online entertainment applications such as game and video and so on. Examples of the cloud service providers are SalesForce.com (SFDC), Google, Microsoft, Oracles, NetSuite and IBM [15].
Platform as a Service (PaaS) model provides a complete development platform on the cloud as a service to customer. This platform provides everything to users that are used for designing, development, testing, and deployment applications to the cloud. This model is used to construct a higher level of service i.e. SaaS applications/services and so on. By using this, the clients can create web applications without organizing the hardware and software services on their own computer. They have full control over these applications to run and deploy. Services providers may use integrated OS, middleware, application software to construct a platform; for consumer side, API (application programming interface) brings package service to users for user side and users use the Platform through API. Key examples are GAE (Google App Engine), force.com (from salesforce.com), Microsoft's Azure [15]. The cost of PaaS is very low as compare to software development platform based on the data center.
Infrastructure as a Service (SaaS) consists of a hardware related services offered by cloud vendor. These services include some kind of storage services (database or disk storage), networks, virtual servers and other basic computing resources where user can deploy and run arbitrary software (i.e. operating system and applications). The user does not need to purchase the required infrastructure such as servers, network resources or data center. Consumers need to pay only for the time period in which they use the service. As a result, users can achieve very fast service delivery with low cost. The most known vendors that provide Infrastructure as a service are Amazon EC2 and S3, Rackspace Cloud Servers, Sun Microsystems Cloud Services, Flexiscale ,Terremark and Dropbox.
The above classification of service models is well accepted in the industry. But there are more granular clasification on the basis of service provided [21]. In
4. Commercial product of cloud computing
These days, cloud computing is in an era of quick development, so it is clear that the new features and contents continue to discover. The companies which offer Cloud computing services come in all shapes and sizes. There are some companies such as Amazon, Google, Microsoft, Salesforce, IBM and Yahoo which are pioneers in cloud computing market. There are many companies which are attempting to grip in the market of cloud computing. We will give a brief introduction of some leading Vendors of services.
In the area of Infrastructure as a Service Amazon is pioneer and market leader among the cloud vendors. Amazon has a set of cloud services called Amazon Web Services [16]. These services are: Amazon Elastic Compute Cloud (EC2), Amazon S3(simple storage service), Amazon SimpleDB. EC2 provides computing servers on rent basis [1]; S3 provides data storage using a simple web interface on rent basis [27]; SimpleDB is non-relational database and provides web based service for running queries on structured data in real time [4]. Google is obviously a leader in the cloud computing space. Google provides the following cloud computing services: Software as a Service (SaaS) Google offers GMail, Google Docs, Picasa, Google Calendar and Google Group; Platform as a Service (PaaS) Google offers Googles AppEngine (GAE) which is a developer platform based upon Java and Python [29]. By using GAE a user can build a basic web application very quickly. Like other key cloud computing providers, IBM is also a leading Vendor in the Cloud computing area. SaaS IBM offers LotusLive iNotes, an email service based on web that provides messaging and calendaring facilities to users. Infrastructure as a Service cloud computing IBM offers Smart Business Storage Cloud for data storage and Computing on Demand (CoD) for data computing.
Salesforce.com is pioneer in Software as a Service. It was the first company which built a very successful product Customer Relationship Management on the cloud. CRM contains the information related to Marketing and Management. PaaS, Salesforce.com officers a development platform called force.com [9]. As discussed earlier Microsoft is also a pioneer company in the field of Cloud Computing. Microsoft offers BPOS (Business Productivity Online Suite) in SaaS space. In the Platform as a Service Microsoft provides a platform called Microsoft Azure [28]. Microsoft Azure offers a development platform which is based upon .Net.
5. Security challenges
Currently, Cloud Computing can be used almost everywhere and provides many benefits to companies, individual users and government organizations. It provides efficient, elastic and cost effective services environment to concerned customers. However, Cloud Computing also makes the interest of attackers and increases many security concerns. Security researchers, hackers and attackers have exposed that this model can be compromised and is not fully secure [33]. Gartner
In-Door threats: Even having the most advanced computer security and firewalls to your computer system is still vulnerable to inside threats [32]. It is a recognized fact that most of the security threats occur from inside an organization. In public cloud computing model, external customers store and process sensitive data on the cloud. If the vendor side, staff cannot be trusted that means the data of user side is unsafe. Thus there is possibility to violate two main security properties of data: Integrity and confidentiality. If any staff member misuses this data then reputation of Vendor will degrade also. One of the worlds major technology companies, Google recognizes the value of reputation for security matter as a key of success [23].
External Malicious Attacks: All the services in cloud computing environment are available on web; exchange of information between consumer and vendor is based on internet and for sometime is outside the domain of consumer and vendor. In this duration, due to the open structure of public cloud, it attracts the intruder; the data can also be under the jurisdiction of intruder. There are some external threats which include: man-in-the-middle, IP spoofing, denial of service attacks, Trojan Horses and Malware TCP Hijacking, Dumpster Diving, Password Guessing, Replay, etc [2]. These types of threats may violate the Integrity and confidentiality of data.
Virtualization technology Related Security: Virtualization is a core technique in cloud environment, which offers important cloud characteristics in Infrastructure as a Service which are: quick elasticity, resource pooling and location independence. It allows abstraction of computing resources, and creates several logical virtual machines (VMs) over a single physical machine function. VM refers to a software computer which behaves like a physical computer, also runs an
operating system and applications. It is always difficult to efficiently control several virtual machines running on a same physical machine. Each client operates on his own VM with operating system and all the software, which lead to security vulnerability that can be exploited by an attacker. The risk of virtual machine-to-virtual machine attacks or cooperation of VM is becoming a center for future attacks [11].
Data recovery: Incidentally, clients data may cause damage or loss due to server breakdown or fault in storage device. If this happens, would cloud vendor provides complete restoration, and, if does, how long that process will take [7]?
Long-term Viability: Users of cloud should ensure that the information located on cloud will never become invalid even the service provider (vendor) goes out of business, mixed up or swallow up by a superior company. If this type situation happen, then Is clients information returned and in which format [7]?
Loss of control: When clients locate their data or consume services on cloud, they dont know the exact location of stored data and offered services [25, 31]. Vendor can host their data or service at anyplace inside the cloud. This creates a serious concern as from a client point of view; clients lose control over their very important data and are not alert from any security mechanisms provided by cloud vendors side. How clients data is in unknown place and without any control over it described in [14].
Data locality: In the cloud computing environment, clients dont know where their vital data is stored, and client has no control over it, which may be an issue when an investigation occurs then who has the jurisdiction over that data. Another question picked up by Gartner [7]: Does the cloud vendor allow providing any control over the location of data?
There is no doubt that could computing can make live of its costumers easy by providing the services anywhere and every time on web. But in spite of providing many advantages to the costumers, its customers have to face a biggest challenge, which is security in cloud environment [30]. According to IDC survey [18], 74% managers and CIOs of IT industry believed that the security issues in cloud computing is major challenge that hinders customers from using services of cloud computing. According to the survey conducted by Garter [7], greater than 70% CTOs of IT believe that data security and privacy in cloud computing environment are the primary reason not to use the cloud computing services. There are may security challenges mentioned in [20, 22, 26]. Even though cloud vendors publicize the reliability and security of their services, but in reality, according to many survey related to cloud security, cloud services
are not as reliable and safe as vendors claim; but opposite this, described in [34], during system upgrade, Amazon Elastic Compute Cloud (EC2) crashed in April 2011. In the same month, Sony PlayStation Network was broke by hackers, resulting that personal information of 77 million people around the world was exposed. There is much information related to the security leakage of cloud vendors in [34, 35]. Due to the open structure and multi-tenant characteristic of cloud computing, the models of cloud computing as compared with the traditional IT environment may face different risks and challenges. So cloud computing environments have to face these traditional security issues. One more thing, so far cloud computing paradigm has no standard architecture and no standard world-wide accepted protocol to enhance the confidence of customers toward cloud computing world.
6. Conclusions and Future work
We discussed a novel technology: Cloud Computing, which can definitely make the business world more efficient and convenient by offering services on demand over internet. In spite of major benefits provided by cloud computing, it is not fully matured. More and more companies want to join into Cloud environment to provide services for a huge amount of users. Instead of various services provided by leading companies, we know that era of cloud computing is coming now. It will be good for user, because they would have lots of alternatives to choose services. However, security and privacy issues in cloud computing are major challenges that hinder customers to adopt the services of cloud computing. But there is no doubt that cloud computing is going toward a bright future and likely to be very useful to public user. Future work can be performed in the following areas of cloud computing: 1) to construct standardizing security protocols, 2) to construct standardizing architectural method, 3) To develop standardizing world-wide accepted protocol.
7. References
Amazon, Ec2, http://aws.amazon.com/ec2/, 2008.
Huiming Yu, N. Powell, D. Stembridge, X. Yuan, Cloud computing and security challenges, Proc. of the Annual Southeast Conference, 2012, pp. 298-302.
A Platform Computing Whitepaper, Enterprise Cloud Computing:Transforming IT, Platform Computing, pp6, viewed 13 March 2010.
Amazon, Simpledb, http://aws.amazon.com/simpledb/, 2008.
Gens F, 2009, New IDC IT Cloud Services Survey: Top Benefits and Challenges,IDC eXchange, viewed 18 February 2010, from <http://blogs.idc.com/ie/?p=730>.
Global Netoptex Incorporated, 2009, Demystifying the cloud. Important opportunities, crucial choices, http://www.gni.com, pp 4-14, viewed 13 December 2009.
Brodkin J, 2008, Gartner: Seven cloud-computing security risks, Infoworld, viewed 13 March 2009, from http://www.infoworld.com/ d/security-central/gartner-seven- cloudcomputing-security-risks-853?page=0,1
J. Rymarczyk, Virtualization for Data Centers of Today &Tomorrow,http://www07.ibm.com/systems/includes/ cont- ent/migratetoibm/pdf/Virtualization_for_Data_Centers_of_To day_Tomorro-w .pdf
SaleForce, Saleforce crm, http://www.salesforce.com/, 2008.
Dooley B, 2010, Architectural Requirements Of The Hybrid Cloud, Information Management Online, viewed 10 February 2010, from <http://www.information- management.com/news/hybrid-cloudarchitectural- requirements-10017152-1.html>.
Research paper Private Virtual Infrastructure (PVI) Model for Cloud Computing International Journal of Software Engineering Research & Practices Vol.1, Issue 1, Jan, 2011.
Gens F (2008) Defining Cloud Services and Cloud Computing. IDC eXchange, 23 September 2008
P. Mell and T. Grance, The NIST definition of Cloud Computing, National Institute of Standards and Technology (NIST), http://csrc.nist.gov/publications/nistpubs/800-145/ SP800-145.pdf, 2011.
Trusted client to cloud access article http://soaexpressway. wordpress.com /2011/03/01/trusted- client-tocloud-access/
Bhaskar Prasad Rimal, Eunmi Choi, "A taxonomy and survey of cloud computing systems", 2009 Fifth International Joint Conference on INC, IMS and IDC, published by IEEE Computer Society.
Li B et al (2009) EnaCloud: an energy-saving application live placement approach for cloud computing environments. In: Proc of international conf on cloud computing.
Tharam Dillon, Chen Wu, Elizabeth Chang, Cloud computing: issues and challenges, 24th IEEE International Conference on Advanced Information Networking and Applications, 2010, pp. 27-33.
IDC, IT Cloud Services User Survey, 2008.
June 13,2009, http://server.zol.com.cn/183/1830464.html.
H.Mei, J. Dawei, L. Guoliang and Z. Yuan, "Supporting Database Applications as a Service", ICDE'09:Proc. 25thIntl.Conf. on Data Engineering, 2009, pp. 832-843.
Gathering clouds of XaaS! http://www.ibm.com/ develo- per
S. Subashini and V. Kavitha, "A survey on security issues in service delivery models of cloud computing", Journal of Network and Computer Applications, 34(1), 2011, pp 1-11.
ComputerWeekly.com: Top Five Cloud Computing Security. http://www.computerweekly.com/Articles/2009/04/ 24/235782/ top-five-cloud-computing-security-issues.htm#6,
Peeyush Mathur, Nikhil Nishchal, "Cloud Computing: New challenge to the entire computer industry", 1st
International Conference on Parallel, Distributed and Grid Computing, 2010, pp. 223 – 228
ISACA (auditors perspective journal) http:// www.isa- ca.org/Journal/Past-Issues/2009/Volume-6/Pages/Cloud-
Computing-An-Auditor-s-Perspective1.aspx
C. Wang, Q. Wang, K. Ren and W. Lou, "Ensuring data storage security in cloud computing", ARTCOM'10: Proc. Intl. Conf. on Advances in Recent Technologies in Communication and Computing, 2010, pp. 1-9.
A. AWS, S3, http://aws.amazon.com/s3/, 2008.
Windows Azure, www.microsoft.com/azure
Google App Engine, URL http://code.google.com/ appengine
J. Viega, "Cloud computing and the common man", Computer, 42, 2009, pp. 106-108.
Research paper Security Issues and Solutions in Cloud Computing http://wolfhalton.info/2010/06/25/security
-issues-and-solutions-incloud-computing/
Cloud and Telecom security article http://sbin.cn/ blog/2009/11/10/true-or-false-70-of-security-incidentsare- due-to-insider-threats/
Wesam Dawoud, Ibrahim Takouna and Christoph Meinel, "Infrastructure as a service security: Challenges and solutions," 7th International Conference on Informatics and Systems, 2010, pp. 1-8.
Ch. Cachin and M. Schunter, A Cloud Your Can Trust, IEEE Spectrum 48(12), Dec.-2011, pp. 28-51.
D. Chen and H. Zhao, Data Security and Privacy Protection Issues in Cloud Computing, ICCSEE, 2012, pp. 647-651.
International Journal of Engineering Research & Technology (IJERT)
ISSN: 2278-0181
Vol. 2 Issue 2, February- 2013
Leave a Reply
You must be logged in to post a comment.
To read this content please select one of the options below:
Please note you do not have access to teaching notes, analysing the adoption of cloud computing service: a systematic literature review.
Global Knowledge, Memory and Communication
ISSN : 2514-9342
Article publication date: 19 May 2020
Issue publication date: 19 February 2021
The purpose of this paper is to presents an analysis of geographically and disciplinary scattered academic publications of cloud computing (CC) research in information systems. This review aims to understand the research methodology, research frameworks and models, geographical distribution, trends, critical factors and causal relationships associated with cloud computing adoption (CCA).
Design/methodology/approach
Systematic-literature-review using natural language processing is conducted to explore the phenomenon. The relevant research studies are extracted from various online databases using quality-assessment-criteria.
The study is a novel attempt to highlight the differences in critical factors for CCA in different country-settings. Further, the research explores the causal relationships among the identified factors. The findings of this 12-year systematic-review contribute by aiding the providers and potential adopters to devise context-specific strategies for the penetration of cloud services and sound adoption decisions (ADs), respectively. The findings also highlight the prospective avenues of research in the domain for researchers. Using the in-depth analysis, conceptual frameworks have been proposed that can assist in exploring the pre-adoption and post-adoption of CC.
Originality/value
This study contributes to CCA research by providing holistic insights into the methodology, research framework and models, geographical focus, critical factors and causal relationships influencing the AD or intention. The review highlights the unexplored emerging research topics in the field of CCA for future research directions.
- Cloud computing
- Developing countries
- Developed countries
- Cloud services
- Critical factors
- Auto-correlation map
- Vantage point
Acknowledgements
The authors would like to thank the anonymous reviewers and Editor for their constructive comments and support that helped to enhance the quality of the research work.
Sharma, M. , Gupta, R. and Acharya, P. (2021), "Analysing the adoption of cloud computing service: a systematic literature review", Global Knowledge, Memory and Communication , Vol. 70 No. 1/2, pp. 114-153. https://doi.org/10.1108/GKMC-10-2019-0126
Emerald Publishing Limited
Copyright © 2020, Emerald Publishing Limited
Related articles
We’re listening — tell us what you think, something didn’t work….
Report bugs here
All feedback is valuable
Please share your general feedback
Join us on our journey
Platform update page.
Visit emeraldpublishing.com/platformupdate to discover the latest news and updates
Questions & More Information
Answers to the most commonly asked questions here
- Advanced Search
A systematic review on cloud computing
Computer Science Department, Federal University of Bahia, Salvador, Brazil
Informatic Center, Federal University of Pernambuco, Recife, Brazil
- 40 citation
New Citation Alert added!
This alert has been successfully added and will be sent to:
You will be notified whenever a record that you have chosen has been cited.
To manage your alert preferences, click on the button below.
New Citation Alert!
Please log in to your account
Save to Binder
- Export Citation
- Publisher Site
The Journal of Supercomputing
Cloud computing is an ascending technology that has introduced a new paradigm by rendering a rational computational model possible. It has changed the dynamics of IT consumption by means of a model that provides on-demand services over the Internet. Unlike the traditional hosting service, cloud computing services are paid for per usage and may expand or shrink based on demand. Such services are, in general, fully managed by cloud providers that require users nothing but a personal computer and an Internet access. In recent years, this model has attracted the attention of researchers, investors and practitioners, many of whom have proposed a number of applications, structures and fundamentals of cloud computing, resulting in various definitions, requirements and models. Despite the interest and advances in the field, issues such as security and privacy, service layer agreement, resource sharing, and billing have opened up new questions about the real gains of the model. Although cloud computing is based on a 50-year-old business model, evidence from this study indicates that cloud computing still needs to expand and overcome present limitations that prevent the full use of its potential. In this study, we critically review the state of the art in cloud computing with the aim of identifying advances, gaps and new challenges.
Index Terms
Software and its engineering
Software organization and properties
Software system structures
Distributed systems organizing principles
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Full Access
- Information
- Contributors
Published in
Copyright © Copyright © 2014 Springer Science+Business Media New York
In-Cooperation
Kluwer Academic Publishers
United States
Publication History
- Published: 1 June 2014
Author Tags
- Virtualization
- On-demand business model
- Service layer agreement
- Cloud computing
Funding Sources
Other metrics.
- Bibliometrics
- Citations 40
Article Metrics
- 40 Total Citations View Citations
- 0 Total Downloads
- Downloads (Last 12 months) 0
- Downloads (Last 6 weeks) 0
Digital Edition
View this article in digital edition.
Share this Publication link
https://dl.acm.org/doi/10.1007/s11227-014-1089-x
Share on Social Media
- 0 References
Export Citations
- Preview is not available. By clicking download, a new tab will open to start the export process. The process may take a few minutes but once it finishes a file will be downloaded on your browser so please do not close the new tab. Download
- Download citation
- Copy citation
We use cookies to ensure that we give you the best experience on our website.
Please note that Internet Explorer version 8.x is not supported as of January 1, 2016. Please refer to this support page for more information.
- Purchase PDF
Article preview
Introduction, section snippets, references (78), cited by (87), recommended articles (6).
Computers & Industrial Engineering
A systematic literature review of cloud computing use in supply chain integration.
This paper analyzes the current state of research into Cloud Computing and Supply Chain Integration with the objective to identify the findings to date, the areas of study developed and research gaps to provide guidance for future research. For this, a Systematic Literature Review was conducted, with 77 papers addressing the Cloud Computing-Supply Chain Integration relationship identified for analysis. These papers provide evidence of a positive relationship between the adoption of Cloud Computing use in process/activity integration, technology/system integration, and supply chain partner integration. The reviewed literature also indicates that Cloud Computing use in supply chain can also have an impact on the integration of the supply chain’s information, physical and/or financial flows.
There is currently a broad consensus among the scientific community as to Information Technology’s (IT) role as a source of competitive advantage. In this regard, IT is not a tool that has a direct impact on results, but does so through other company resources and capabilities; and Supply Chain Integration (SCI) is one of these capabilities (Bruque, Moyano, & Maqueira, 2015). Likewise, a technological trend, named Cloud Computing (CC), emerged to modify the use of IT in a more effective way. In CC (Buyya et al., 2009, Buyya et al., 2011), resources are located in virtualized and distributed environments geographically disperse. They can be accessed on an on-demand basis through web-based technologies, combining internet connectivity and pay-per-use systems (Winans & Brown, 2009) in a new business model for IT provisioning (Son et al., 2014, Maqueira et al., 2017). The National Institute of Standards and Technology, US department of commerce defines Cloud Computing as a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g. networks, servers, storage, applications and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction (Mell & Grance, 2011).
CC is composed of five essential characteristics, including on-demand self-service, broad network access, resource pooling, rapid elasticity and measured service (Mell & Grance, 2011). Three different types of service models can be distinguished in Cloud Computing: Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS) (Ryan & Loeffler, 2010). IaaS involves sharing data or IT infrastructure that can be used as a service; PaaS entails providing a complete platform for application development and deployment; and SaaS involves delivering software online as an on-demand service. These service models can be organized into four deployment models: Private Cloud, internally in a single organization; Community Cloud, enabling a group of business partners to share key resources; Public Cloud, deployed by providers who offer their services to the business community; and Hybrid Cloud, which combines public and private models (Ryan and Loeffler, 2010, Mell and Grance, 2011). CC offers a number of advantages over traditional IT models, including faster data transactions, elasticity, resource-sharing, pay-per-use, flexibility, ease of configuration, low IT deployment cost, the need for data centers, and increased IT performance (Marston et al., 2011, Wu et al., 2013, Jede and Teuteberg, 2015, Bruque et al., 2015, Liu et al., 2016). However, CC is not without its barriers, including concerns about data security and privacy, uneven service availability, limited compatibility with existing applications and systems, and a weak regulatory framework (Oliveira et al., 2014, Doherty et al., 2015, Vermula and Zsifkovits, 2016).
Supply Chain Integration (SCI) is conceptualized as the degree to which a company collaborates with its supply chain partners and collaboratively manages intra-organizational and inter-organizational processes, in order to achieve effective and efficient integration of physical, information and financial flows (Flynn, Huo, & Zhao, 2010). SCI emerges as an important field of interest and involves the strategic alignment of functions and processes within an organization and between supply chain members (Chen et al., 2009, Kumar et al., 2017). In fact, a highly integrated supply chain involves interaction and collaboration between company, customers and suppliers, and depends on a high degree of information exchange, mutual dependence and joint actions between supply chain members (Harland et al., 2004, Huang and Huang, in press). The cross-functional border integration of processes and activities, involving suppliers and customers in supply chains, is considered a key to achieving competitive advantage (Littler et al., 1995, Frohlich and Westbrook, 2001, Bruque et al., 2015). For the full potential of SCI to be exploited, it is necessary to integrate flows, processes, activities, technologies and partners in the chain (Troyer and Cooper, 1995, Fabbe-Costes and Jahre, 2008). Integration is achieved by integrating information, physical, and financial flows (Rai, Patnayakuni, & Seth, 2006).
Companies are rapidly adopting CC in their business processes and in all their functional areas, and the potential for the application of these technologies in the supply chain is very high (Bruque et al., 2015). This has resulted in an emerging line of research that focuses on the effects that derive from the application of CC technologies in the supply chain (Schramm et al., 2011, Casey et al., 2012, Azevedo et al., 2013, Jede and Teuteberg, 2015, Li, Luo, et al., 2015, Vermula and Zsifkovits, 2016). So, recent research addresses the CC-SCI relationship (Bruque et al., 2015, Bruque et al., 2016), which is an even more specific line of research.
Likewise, the amount of research in the area has grown substantially lately. Most of this research corresponds to theoretical discussions on the role of CC in SCI (Abidi et al., 2014, Jede and Teuteberg, 2015, Pérez-Salazar et al., 2017) but there has also been an increase in empirical research that merits attention by academics and practitioners (Devaraj et al., 2007, Bruque et al., 2015, Bruque et al., 2016). However, results to date regarding CC-CSI relationship are diffuse, not fully understood, and with many mechanisms and effects that have only been addressed in part or not at all. Thus, further and fuller attention is required to understand this CC-SCI relationship (Bruque et al., 2015). This improved knowledge may affect the way researchers approach CC-SCI and can be very useful for the design of future research endeavors in the area. Also, company managers may be informed of the potential managerial implications, advantages and risks related to the CC-SCI relationship. A tangible need to develop a better and more focused understanding of the CC-SCI relationship can therefore be stated to exist.
Therefore, the objective of this study is to scrutinize previous research that examines the CC-SCI relationship to identify the findings to date, lines of study developed and gaps to advance research in the area. Based on a literature review, this paper provides an overview of the possible relationships between CC and SCI and uses a multidimensional structure to categorize the studies. The study’s systemic and integrative approach enables multiple aspects of integration to be addressed, with the focus on integrating processes and activities, technologies and systems, and partners. It is not limited to any particular aspect of integration (e.g., Manufacturing integration, as in Helo, Suorsa, Hao, and Anussornnitisarn (2014), or supply chain collaborative strategies, as in Duan and Liu (2016)) but, rather, gives a broader view of CC-SCI. This paper also identifies, from existing literature, gaps and directions for future research.
The aim, therefore, is to contribute to improving knowledge of the CC-SCI relationship through a Systematic Literature Review and analysis of papers that address the CC-SCI relationship published in scientific journals.
This paper has been organized into five sections. After this introduction, the second section describes the methodology. In the third section, the results obtained are presented and discussed. Section four presents the conclusions and, lastly, section five provides a summary of the paper.
Methodology
In order to achieve the research objective (Biel and Glock, 2016, Scheidegger et al., 2018) the Systematic Literature Review (SLR) technique has been used (Denyer & Tranfield, 2009). Following the steps established in this technique (Denyer & Tranfield, 2009), the existing literature on the investigated issue has been identified. The literature analysis and synthesis allows to identify the existing findings, research directions and gaps.
Systematic Literature Review (SLR) is a tried and tested
Results and discussion
The analysis of the 77 selected papers allows to identify the current state of knowledge of CC effect on SCI (answer RQ1) and gaps detected and future research directions (answer RQ3). Studies were grouped by three mains topic. For each main topic, the research directions were identified and finally the papers were classified into research sublines (answer RQ2). These results are shown in detail below.
Conclusions
The major findings of this paper refer to the main relationships that exist in the CC-SCI area and give readers an overview of the full potential of CC use in SCI. The study findings are intended for both researchers and company managers, and can help them understand what has been studied, trends in the area, and knowledge gaps (areas barely explored or not at all). On the one hand, researchers will be able to orientate their studies toward improving knowledge and bringing to light new uses for
A Systematic Literature Review (SLR) of 77 papers was conducted to identify, select, review and synthesize the relevant literature on Cloud Computing and Supply Chain Integration, and detect extant gaps and future research lines.
Interest in the CC-SCI topic is growing in different industrial areas and it has been approached from several methodological perspectives by multi-country authors.
CC has a strong impact on process and activity integration, by enhancing technological resource integration
Acknowledgments
The authors acknowledge the financial support of Conselho Nacional de Desenvolvimento Científico e Tecnológico ( CNPq ) of Brazil; the Spanish Ministry of Economy and Competitiveness Research Project ECO2015-65874-P ; and the University of Jaén through its Research Support Plan (2017 and 2018). The authors are also grateful for the work and suggestions from the editor and anonymous reviewers, who have contributed to significantly improving the paper.
Cloud-assisted industrial cyber-physical systems: An insight
Microprocessors and microsystems, iot-enabled dynamic service selection across multiple manufacturing clouds, manufacturing letters, a mobile payment mechanism with anonymity for cloud computing, journal of systems and software, from cloud computing to cloud manufacturing, robotics and compute-integrated manufacturing, development of a cloud-based platform for footprint assessment in green supply chain management, journal of cleaner production, closed-loop design evolution of engineering system using condition monitoring through internet of things and cloud computing, computer networks, cloud-based design and manufacturing: a new paradigm in digital manufacturing and design innovation, computer-aided design, cloud manufacturing: strategic vision and state-of-the-art, journal of manufacturing systems, ubiquitous manufacturing system based on cloud: a robotics application, robotics and computer-integrated manufacturing, from cloud manufacturing to cloud remanufacturing: a cloud-based approach for weee recovery, towards smart factory for industry 4.0: a self-organized multi-agent system with big data based feedback and coordination, a collaborative and integrated platform to support distributed manufacturing system using a service-oriented approach based on cloud computing paradigm, sdmsim: a manufacturing service supply–demand matching simulator under cloud environment, reprint of integration of logistics and cloud computing service providers: cost and green benefits in the chinese context, transportation research, cloud computing technology: reducing carbon footprint in beef supply chain, international journal of production economics, cloud computing and its impact on economic and environmental performance: a transaction cost economics perspective, decision support systems, extended study of network capability for cloud based control systems, adaptation of incremental sheet forming into cloud manufacturing, cirp journal of manufacturing science and technology, swtrack: an intelligent model for cargo tracking based on off-the-shelf mobile devices, expert system application, a knowledge-based social networking app for collaborative problem-solving in manufacturing, the challenge of networked enterprises for cloud computing interoperability, computers in industry., product modeling from knowledge, distributed computing and lifecycle perspectives: a literature review, computers in industry, a semantic web-based framework for service composition in a cloud manufacturing environment, multi-granularity resource virtualization and sharing strategies in cloud manufacturing, journal of network and computer applications, resource virtualization and service selection in cloud logistic, product whole life-cycle and omni-channels data convergence oriented enterprise networks integration in a sensing environment, framework and development of fault detection classification using iot device and cloud environment, cloud-enabled real-time platform for adaptive planning and control in auction logistics center, computers and industrial engineering, cloud-based materials tracking system prototype integrated with radio frequency identification tagging technology, automation in construction, toward a cloud-based manufacturing execution system for distributed manufacturing, ict in multimodal transport and technological trends: unleashing potential for the future, the role of wearable devices in meeting the needs of cloud manufacturing: a case study, manufacturing in the cloud: a human factors perspective, international journal of industrial ergonomics, scalable real-time olap on cloud architectures, journal of parallel and distributed computing, modeling of manufacturing service supply-demand matching hypernetwork in service-oriented manufacturing systems, a flexible qos-aware web service composition method by multi-objective optimization in cloud manufacturing, a cloud computing platform for erp applications, applied soft computing, a novel system for cloud-based micro additive manufacturing of metal structures, journal of manufacturing processes, a hybrid approach to explore the critical criteria of online supply chain finance to improve supply chain performance.
With the rapid development of information and internet technologies, online supply chain finance is becoming increasingly important in improving supply chain performance from many perspectives, including capital and information. To fully understand the role of online supply chain finance, it is necessary to comprehensively assess the criteria of online supply chain finance that affect supply chain performance. Meanwhile, given the lack of relevant theoretical research and methodologies, this study proposes a hybrid approach that integrates fuzzy set theory, interpretive structural modelling and a Bayesian network to assess and identify the critical criteria. The results show that criteria such as the development of the supply chain industry, incentive mechanisms, e-commerce platforms and the quality of small and medium-sized enterprises are predominant in improving supply chain performance. Finally, some new findings and corresponding suggestions are also provided.
To adopt or not to adopt? The determinants of cloud computing adoption in information technology sector
This research is mainly focused on the adoption of cloud computing in the information technology (IT) industry of a developing country, Pakistan by using the theoretical lens of technology acceptance model (TAM) and Elaboration Likelihood Model (ELM). Cloud computing, being one of the latest technologies in the field of IT, has been recently adopted by organizations around the globe, although developing nations have recently started using this technology in their supply chain processes. This study involved the employees of IT industry working in the capital city of Pakistan, i.e. Islamabad. Sample respondents consisted of 213 employees of the IT based organization. Data was collected online by employing structured questionnaires based on past literature. The results revealed that there exists a positive and significant relationship between perceived security, argument advantage, source credibility and perceived usefulness. Additionally, the outcome of the study supported the significant relationships between perceived usefulness and attitude towards adoption of cloud computing, perceived usefulness and intention to adopt cloud computing, and attitude towards cloud computing and intention to adopt cloud computing. The research study has managerial and practical implications. It is one of first of its kind that explores some of the factors leading to adoption of cloud computing in of IT companies in Pakistan.
Information sharing in supply chains – Interoperability in an era of circular economy
In order to realize the goals of Industry 5.0 (I5.0), which has data interoperability as one of its core principles, the future research in the Supply Chain (SC) visibility has to be aligned with socially, economically and environmentally sustainable objectives. Within the purview of circular economy, this paper indicates various aspects and implications of data sharing in the SCs in light of the published research. Taking into consideration the heterogeneity of data sources and standards, this article also catalogs all the major data-sharing technologies being employed in sharing data digitally across the SCs.
Drawing on the published research from 2015 to 2021, following the PRISMA framework, this paper presents the state of research in the field of data sharing in SCs in terms of their standardization, optimization, simulation, automation, security and more notably sustainability. Using the co-occurrence metric, bibliometric analysis has been conducted such that the collected research is categorized under various keyword clusters and regional themes. This article brings together two major themes in reviewing the research in the field. Firstly, the bibliometric analysis of the published articles demonstrates the contours of the current state of research and the future possibilities in the field. Secondly, in synthesizing the research on the foundations of sustainability within the CRoss Industry Standard Process for Data Mining (CRISP-DM) framework, this article deals with various aspects and implications of information sharing in the SCs. By bringing these two themes together, this paper affords a prospective researcher with the research vis-à-vis the information sharing in SC, starting from the actual data standards in use to the modality and consequence of their application within the perspective of the circular economy. This article, in essence, indicates how all the aspects of data sharing in SCs may be brought together in service of the paradigm of I5.0.
A literature review towards theories and conceptual models of empirical studies on supply chain integration and performance
Supply chain integration (SCI) has attracted much attention from academia and industry. Empirical studies have employed different theories and have built various conceptual models to probe the effect of SCI on performance. Our study sets out to conduct a review on the SCI-performance relationship by combining the perspectives of theories and conceptual models. Our purpose is to enrich the theoretical as well as the practical understanding of SCI. Based on the review of 160 empirical studies, we find ten commonly used theories and eight conceptual models regarding the SCI-performance relationship. We discuss how these theories are applied in establishing different conceptual models and obtain nuanced theoretical and practical insights by looking at the combination of theories and conceptual models. Our study contributes to a comprehensive understanding of how and why SCI influences performance and better informs managers regarding how to implement SCI.
The link between information and digital technologies of industry 4.0 and agile supply chain: Mapping current research and establishing new research avenues
The use of Industry 4.0 (I4.0) Information and Digital Technologies (IDT) has given rise to new opportunities and challenges for designing and managing agile supply chains. Therefore, this study aims to investigate the role and implications of IDT of I4.0 for the Agile Supply Chain (ASC) strategy through a systematic literature review of 123 identified papers. The literature has been classified into three research lines based on the Technology Life Cycle: (1) Mature IDT of I4.0 and ASC; (2) Emerging IDT of I4.0 and ASC, and (3) A generic approach to the role and implications of IDT of I4.0 and ASC. This categorization gives an in-depth analysis of the relationship between the IDT of I4.0 and Agile Supply Chain and helps to clarify the way that the research has evolved. Among other findings, the results show that there is a prominent relationship between different types of IDT of I4.0 and ASC. These technologies can support the ASC by improving abilities to sense and respond to market changes and customer demands. The paper also discusses the gaps found in the literature, presents an ASC 4.0 model enabled by IDT of I4.0, and proposes new opportunities for future research.
Supply chain traceability systems—robust approaches for the digital age
Traceability systems play an important role in the digital transformation of the supply chain. This chapter examines the principal issues on the what, why, and how of achieving digital supply chain traceability in relation to data and technology. We consider the overlapping definitions of visibility, traceability, tracking, tracing, and transparency. We highlight factors driving the need to achieve higher levels of traceability, including regulatory demands, business incentives, and customer concerns and preferences. The emergence of global standards related to traceability is noted. The types of information required to successfully track and trace products in a digital supply chain are explained, as well as the technologies applied to collect, follow, and share information, including radio frequency identification, Internet of Things, and blockchain. The challenges around cybersecurity, standards, data quality, integrating new technologies, and potentially competing interests among stakeholders are discussed. We examine the traceability of wood products, which are important globally and raise significant sustainability challenges. The case illustrates how technical solutions can be incorporated into the traceability system to respond to the needs and challenges of stakeholders. Further research is needed on the technical, policy, and business strategy solutions to address common data and technology challenges for effective traceability systems.
Crane-operated warehouses: Integrating location assignment and crane scheduling
Crane-operated warehouses constitute an essential asset for the many industries which must temporarily store products on their way from manufacturers to consumers. Such warehouses are a practical necessity rather than an explicitly desired service and they introduce significant operational costs which should be minimized. The problem addressed by the current paper, the Crane-operated Warehouse Scheduling Problem (CWSP), concerns the location assignment of input products and the scheduling of cranes for product movement in such warehouses. Several constraints are associated with the problem, for example certain products should not be stored close to each other (due perhaps to a difference in temperature or aroma) and cranes must respect operational safety distances between each other in order to prevent dangerous collisions. The present paper explores a novel methodology which combines these two decisions – location assignment and crane scheduling - instead of solving them sequentially. In addition to mathematical formulations for location assignment and crane scheduling, both an integrated mathematical formulation and a fast heuristic are presented for the CWSP. The quality of the mathematical formulation and the heuristic are compared against the conventional sequential approaches. Experimentation upon an extensive range of instances show significantly improved results are attainable when integrating location assignment and crane scheduling, despite some (expected) increase in computational time.
Choice-based dynamic time slot management in attended home delivery
E-grocers with an attended home delivery service model operate in a highly competitive market characterized by thin profit margins. To ensure a profit-maximizing delivery schedule, the requirements for the joint management of demand and the vehicle routes are substantial. Therefore, we study an e-grocer’s operational problem of managing demand by means of dynamic time slot allocation. The purpose of dynamically allocating time slots is to influence customers’ choices by offering a selection of time slots to a customer request, such that the overall expected profit of the resulting delivery schedule is maximized. The time slot offer decisions mainly depend on a request’s opportunity cost. Hence, we first propose a mixed-integer linear program to approximate this opportunity cost, which scales linearly with the number of decision variables. In this approximation, we consider the consequences of expected time slot offer decisions for future customers on the final delivery schedule. We explicitly incorporate customer choice behavior using a generalized attraction model. Second, we propose a non-linear binary program and its linearization based on the underlying choice model to make time slot offer decisions using the approximated opportunity cost. Due to the formulation’s structural properties, it can be efficiently solved. In a computational study, we show the superiority of our approach in comparison to benchmarks applied in the academic literature and its applicability in an online environment.
Fitting activity distributions using human partitioning and statistical calibration
Many project management and scheduling studies have modelled activity durations as a range of values to express the stochastic nature of projects in progress. A wide variety of simulation models have been proposed that all rely on pre-defined statistical probability distributions for the durations of project activities. Ideally, these distributions reflect the real stochastic nature of the activities to assure that the simulations imitate the expected reality in the best possible way. However, the distributions are often selected ad hoc, relying on a class of distributions that are often used in the statistical literature, but without having much links with the features of real projects. Recently, a calibration method has been proposed in literature and validated on a set of 24 projects that makes use of real project data to derive realistic statistical distributions. This paper builds further on the validation of this calibration method in three different ways. First, the procedure is now successfully used on a set of 125 projects (for which 83 could be used for the final analysis) from different sectors. Secondly, the procedure has been extended with a partitioning step performed by humans with experience in the particular project. Finally, some procedural extensions have been proposed to test the necessity of each step of the procedure.
Improved decisions for marketing, supply and purchasing: Mining big data through an integration of sentiment analysis and intuitionistic fuzzy multi criteria assessment
This study proposes a novel decision support system for product ranking problems which integrates multi criteria decision making (MCDM) and aspect level sentiment analysis techniques. The main purpose of the developed methodology is to rank the alternative products taking into account a set of product criteria and the customer comments related to these criteria posted on websites to recommend the most appropriate alternative to potential customers. The decision support system comprises two stages, in the first stage, the online customer reviews are transformed into customer satisfaction scores through aspect level sentiment analysis to obtain performance scores corresponding to alternative products, whereas the second stage deals with ranking the alternative products via a novel MCDM methodology, namely “IF-ELECTRE integrated with VIKOR” according to the performance scores obtained in the first level. Intuitionistic fuzzy sets (IFSs) are utilized to effectively represent the customer reviews including hesitant expressions in decision matrix. The weights of criteria (the product aspects of significant importance for customers) are determined using entropy method. The applicability of the developed approach is explored by a case study, in which customer reviews about hotel experiences are evaluated using lexicon based sentiment analysis and alternative hotels are ranked according to the findings from the sentiment analysis by the Intuitionistic fuzzy (IF)-ELECTRE integrated with VIKOR methodology.
Cloud computing and trust evaluation: A systematic literature review of the state-of-the-art mechanisms
Cloud computing is a model to enable the convenient access to the network request for sharing the groups of configurable calculating resources. In this environment, confidences are insufficient for the customers to identify the trustworthy cloud service providers. Therefore, in this system, an important challenge is assessing the trustworthiness to enable the users for choosing the trustworthy resources in the cloud infrastructure. However, in the cloud environments, despite the significance of the trust mechanisms and methods, the comprehensive and systematic research and study about the background of the trust evaluation methods between the cloud providers is rare. Hence, in this paper, we analyzed the trust evaluation state of the art mechanisms which are used in the cloud environment so far. Also, we analyzed and compared them in terms of integrity, security, reliability, dependability, safety, dynamicity, confidentiality, scalability, and giving a suggestion for some future research. Also, this article displays a systematic literature review (SLR) on the trust evaluation mechanisms in the cloud environments up to the end of March 2017. We identified 224 articles, which are reduced to 28 primary ones through our article selection process. By presenting the state-of-the-art information and the challenges issues, this survey will directly support academics, researchers, and professionals in their understanding of changes in the trust evaluation mechanisms in the cloud environments.
Assessing cloud computing value in firms through socio-technical determinants
While cloud computing is touted as a promising information technology advancement, predictions of its value are inconclusive. This research investigates the impact of cloud computing within-firm and across-firm. Drawing on the resource-based view and sociotechnical theory, technical attributes and social attributes of cloud computing are identified to impact firm performance via primary and support use. Results from data collected from 513 firms show varying effects of technical and social attributes in primary use and support use, which help create value and better performance. Such effects also are found to differ between firms in service and manufacturing sectors.
IMAGES
VIDEO
COMMENTS
Cloud computing is an ascending technology that has introduced a new paradigm by rendering a rational computational model possible.
Cloud computing uses the concept of pay as per use basis where users do not need to pay for infrastructure, installation and its maintenance. Anyone can access
The purpose of this study is to analyze and classify the contributions of the studies published in cloud computing field. The cloud literature
Cloud computing benefits both cloud services providers (CSPs) and consumers. The security challenges associated with cloud computing have been
this need, we have conducted a systematic review of cloud computing in eHealth. We searched ACM. Digital Library, IEEE Xplore, Inspec, ISI Web of Science
Research Institute of Network and Information Security, Shenzhen University, Shenzhen 518060, China. 2 College of Computer Science and Software
Cloud computing represents a new era for delivery and utilization of the services over the Internet. Clouds are a large pool of easily usable and accessible
Analysing the adoption of cloud computing service: a systematic literature review - Author: Mahak Sharma, Ruchita Gupta, Padmanav Acharya.
Cloud computing is an ascending technology that has introduced a new paradigm by rendering a rational computational model possible.
This paper analyzes the current state of research into Cloud Computing and Supply Chain Integration with the objective to identify the findings to date, the