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User-Centric Cloud Service Broker

by Hanan Elazhary
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 154 - Number 7
Year of Publication: 2016
Authors: Hanan Elazhary
10.5120/ijca2016912216

Hanan Elazhary . User-Centric Cloud Service Broker. International Journal of Computer Applications. 154, 7 ( Nov 2016), 28-35. DOI=10.5120/ijca2016912216

@article{ 10.5120/ijca2016912216,
author = { Hanan Elazhary },
title = { User-Centric Cloud Service Broker },
journal = { International Journal of Computer Applications },
issue_date = { Nov 2016 },
volume = { 154 },
number = { 7 },
month = { Nov },
year = { 2016 },
issn = { 0975-8887 },
pages = { 28-35 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume154/number7/26505-2016912216/ },
doi = { 10.5120/ijca2016912216 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:59:38.328050+05:30
%A Hanan Elazhary
%T User-Centric Cloud Service Broker
%J International Journal of Computer Applications
%@ 0975-8887
%V 154
%N 7
%P 28-35
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cloud computing technology has gained enormous attention due to its promising capabilities such as virtualization, elasticity and the pay-per-use paradigm. Theoretically, cloud computing can offer Everything as a Service (XaaS). Selecting suitable cloud services matching the Quality-of-Service (QoS) requirements of the user is one of the prominent problems in the literature. A considerable number of research studies attempted to address this problem from different perspectives such as service discovery, service matching and ranking (against QoS requirements of the user) in addition to QoS evaluation and monitoring. In this paper, we argue that we need to integrate all those functionalities to help the cloud service user make more informed selection decisions. Accordingly, we propose a comprehensive user-centric Cloud Service Broker (CSB). We describe the architecture of this broker and discuss how it integrates and orchestrates the different required functionalities. We also discuss different possible methods to realize and implement each of its modules and pinpoint open points of research that need to be explored further. As a proof of concept, we present an example prototype implementation of CSB and discuss a case study using this prototype to justify the advantage of the integration. Towards this goal, we propose a novel evaluation-aware matching and ranking technique that integrates cloud services evaluation results with their matching and ranking against the user QoS requirements for more informed selections of suitable cloud services by taking into consideration the credibility of the cloud service providers.

References
  1. Foster, I., Zhao, Y., Raicu, I., and Lu, S. 2008. Cloud computing and grid computing 360-degree compared. In Proceedings of IEEE Grid Computing Environments Workshop, Austin, TX, USA, (2008).
  2. Mell, P. and Grance, T. 2011. The NIST definition of cloud computing. Special Publication 800-145, National Institute of Standards and Technology (NIST), U.S. Department of Commerce, (2011).
  3. Duan, Y., Fu, G., Zhou, N., Sun, X., Narendra, N. and Hu, B. 2015. Everything as a Service (XaaS) on the Cloud: Origins, current and future trends. In Proceedings of the 8th IEEE International Conference on Cloud Computing, New York, USA, (2015), 621-628.
  4. Elazhary, H. 2014. Cloud computing for Big Data. MAGNT Research Report (2014).
  5. Elazhary, H. 2015. A cloud-based framework for context-aware intelligent mobile user interfaces in healthcare applications. Journal of Medical Imaging and Health Informatics 5(8) (2015) 1680-1687.
  6. Youssef, A. 2012. Exploring cloud computing services and applications. Journal of Emerging Trends in Computing and Information Sciences 3(6) (2012).
  7. Garg, S., Versteeg, S., and Buyya, R. 2013. A framework for ranking of cloud computing services. Future Generation Computer Systems 29 (2013) 1012-1023.
  8. Brock, M. and Goscinski, A. 2011. Enhancing Cloud computing environments using a cluster as a service. In: Cloud Computing: Principles and Paradigms, John Wiley & Sons, (2011), 193-219.
  9. Liu, D., Xing, W., Che, X., and Bao, P. 2015. A centralized service discovery approach for agent-based cloud computing system. The Open Cybernetics & Systemics Journal 9 (2015) 526-535.
  10. Han, T. and Sim, K. 2010. An ontology-enhanced cloud service discovery system. In Proceedings of the International MultiConference of Engineers and Computer Scientists, Hong Kong, (2010).
  11. Gong, S. and Sim, K. 2014. CB-Cloudle: A centroid-based cloud service search engine. In Proceedings of the International MultiConference of Engineers and Computer Scientists, Hong Kong, (2014).
  12. Rehman, Z., Hussain, O., and Hussain, F. 2012. IaaS cloud selection using MCDM methods. In Proceedings of the 19th IEEE International Conference on e-Business Engineering, Hangzhou, China, (2012), 246-251.
  13. Saaty, T. 2008. Decision making with the analytic hierarchy process. International Journal of Services Sciences 1(1) (2008) 83-98.
  14. Behzadian, M., Otaghsara, S., Yazdani, M., and Ignatius, J. 2012. A state-of the-art survey of TOPSIS applications. Expert Systems with Applications 39 (2012) 13051-13069.
  15. Roy, B. 1991. The outranking approach and the foundations of ELECTRE methods. Theory and Decision 31 (1991) 49-73.
  16. Brans, J. and Vincke, P. 1985. A preference ranking organisation method: (The PROMETHEE method for multiple criteria decision-making). Management Science 31(6) (1985) 647-656.
  17. Whaiduzzaman, M., Gani, A., Anuar, N., Shiraz, M., Haque, M., and Haque, I. 2014. Cloud service selection using multicriteria decision analysis. The Scientific World Journal 2014(459375) (2014).
  18. Sun, L., Dong, H., Hussain, F., Hussain, O., and Chang, E. 2014. Cloud service selection: State-of-the-art and future research directions. Journal of Network and Computer Applications 45 (2014) 134-150.
  19. Quinton, C., Romero, D., and Duchien, L. 2014. Automated selection and configuration of cloud environments using software product lines principles. In Proceedings of the 7th IEEE International Conference on Cloud Computing, Alaska, USA, (2014).
  20. Sun, L., Ma, J., Zhang, Y., Dong. H., and Hussain, F. 2016. Cloud-FuSeR: Fuzzy ontology and MCDM based cloud service selection. Future Generation Computer Systems 57 (2016) 42–55.
  21. Youseff, L., Butrico, M., and Da Silva, D. 2008. Toward a unified ontology of cloud computing. In Proceedings of the Grid Computing Environments Workshop, Austin, TX, (2008).
  22. Binz, T., Breiter, G., Leymann, F., and Spatzier, T. 2012. Portable cloud services using TOSCA. IEEE Internet Computing 16(3) (2012) 80-85.
  23. Hwang, K., Bai, X., Shi, Y., Li, M., Chen, W., and Wu, Y. 2015. Cloud performance modeling with benchmark evaluation of elastic scaling strategies. IEEE Transactions on Parallel and Distributed Systems 27(1) (2015) 130-143.
  24. Ferdman, M., Adileh, A., Kocberber, O., Volos, S., Alisafaee, M., Jevdjic, D., Kaynak, C., Popescu, A., Ailamaki, A., and Falsafi, B. 2012. Clearing the clouds: A study of emerging scale-out workloads on modern hardware. In Proceedings of the 17th International Conference on Architectural Support for Programming Languages and Operating Systems, London, UK, (2012).
  25. Huang, S., Huang, J., Dai, J., Xie, T., and Huang, B. 2010. The HiBench benchmark suite: Characterization of the MapReduce-based data analysis. In Proceedings of the IEEE 26th International Conference on Data Engineering, (2010), 41-51.
  26. Smith, W. 2005. TPC-W: Benchmarking an ecommerce solution. Intel, (2005).
  27. Cooper, B., Silberstein, A., Tam, E., Ramakrishnan, R., and Sears, R. 2010. Benchmarking cloud serving systems with YCSB. In Proceedings of the 1st ACM Symposium on Cloud computing, IN, USA, (2010).
  28. Antoniou, A. 2012. Performance evaluation of cloud infrastructure using complex workloads. Master Thesis, Delft University of Technology (2012).
  29. Elazhary, H. and Gokhale, S. 2004(a). Integrating path computation and precomputation for quality-of-service provisioning. In Proceedings of the 9th IEEE International Symposium on Computers and Communications, Alexandria, Egypt, (2004).
  30. Elazhary, H. and Gokhale, S. 2004(b). An integrated approach for QoS provisioning and monitoring. In Proceedings of IASTED International Conference on Parallel and Distributed Computing and Networks, Innsbruck, Austria, (2004).
  31. Rodrigues, G., Calheiros, R., Guimaraes, V., Santos, G., Carvalho, M., Granville, L., Tarouco, L., and Buyya, R. 2016. Monitoring of cloud computing environments: Concepts, solutions, trends, and future directions. In Proceedings of the 31st ACM Symposium on Applied Computing, Pisa, Italy, (2016).
  32. Alfalayleh, M. and Brankovic, L. 2005. An overview of security issues and techniques in mobile agents. IFIP Advances in Information and Communication Technology 175 (2005) 59-78.
  33. Ding, L., Finin, T., Joshi, A., Pan, R., Cost, R., Peng, Y., Reddivari, P., Doshi, V., and. Sachs, J. 2004. Swoogle: A search and metadata engine for the Semantic Web. In Proceedings of the Conference on Information and Knowledge Management, (2004), 652-659.
  34. Selvadurai, J. 2013. A natural language processing based Web mining system for social media analysis. International Journal of Scientific and Research Publications 3(1) (2013).
  35. Myllymaki, J. 2001. Effective Web data extraction with standard XML technologies. In Proceedings of the 10th International World Wide Web Conference, Hong Kong, (2001), 689-696.
  36. Knoblock, C. and Szekely, P. 2015. A scalable architecture for extracting, aligning, linking, and visualizing multi-Int data. In Proceedings of SPIE Next Generation Analyst 9499 (2015).
  37. Herrmann, M., Aslam, M., and Dalferth, O. 2007. Applying semantics (WSDL, WSDL-S, OWL) in Service Oriented Architectures (SOA). In Proceedings of the 10th International Protégé Conference, Budapest, Hungary, (2007).
  38. Schad, J., Dittrich, J., and Quiane-Ruiz, J. 2010. Runtime measurements in the cloud: observing, analyzing, and reducing variance. In Proceedings of VLDB Endowment 3(1) (2010).
Index Terms

Computer Science
Information Sciences

Keywords

Cloud Computing Cloud Service Selection Quality of Service

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