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Efficiency Research of Cloud Based Multimedia Technique with Retrying Fault Tolerance Technique

K. Rengasamy, Vinotha Vinotha

Abstract


A study of retrying for fault tolerance in cloud based multimedia system is analyzed. Especially the response time of the cloud based multimedia system is modeled thereby distribution probability of the response time is derived taking into account the effect of imposing the retrying tasks in case of breakdown in services. Probability distribution of the response time is derived using metric that reflects in a better way the requirements of the customers. Analyze carried out on the percentage of response time that characterizes threshold response time. Inter relationship among the number of service resources, service rate, system performance, task arrival rate are analyzed taking innumerable examples. Cloud based multimedia on retrying for fault tolerance is compared with the check- pointing technique. In the competitive world wireless communication and the growth of multimedia services like real-time conferencing, photo- sharing ,video-on- demand , editing, image search is on high demand for cloud computing. The cloud based multimedia system due to more demand it is required to serve millions of internet and mobile users around the world to access various services on any device, anytime, and anywhere. The cloud computing emerged to facilitate the execution of complicated multimedia tasks and are able to store and process multimedia application and distribute them without any discrepancies thereby eliminating the complexity of software installation and maintenance in users devices.


Keywords


Cloud-Based Multimedia Systems, Percentile of Response Time, Performance Evaluation, Retrying Technique.

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References


I. Foster, Y. Zhao, and I. Raicu, “Cloud computing and grid computing 360-degree compared,” in Proc. Grid Compute. Environ. Workshop, Austin, TX, USA, 2008, pp. 1–10.320 IEEE SYSTEMS JOURNAL, VOL. 8, NO. 1, MARCH 2014

S. Subashini, and V. Kavitha, “A survey on security issues in service delivery models of cloud computing,”J. Netw. Comput. Appl., vol. 34, no. 1, pp. 1–11, Jan. 2011.

M. D. Dikaiakos, D. Katsaros, and P. Mehra, “Cloud computing: Distributed internet computing for IT and scientific research,” Internet Comput., IEEE , vol. 13, no. 5, pp. 10–13, Sep.–Oct. 2009.

Windows Azure. (2012, Jul. 28) [Online]. Available:http://www.microsoft.com/azure

Amazon Elastic Compute Cloud. (2012, Jul. 28)

Apple iCloud. (2012, Jul. 28) [Online]. Available:http://www.apple.com/icloud/

Y. Wu, C. Wu, B. Li, X. Qiu, and F. C. M. Lau, “Cloudmedia:When cloud on demand meets video on demand,” in Proc. 31st Int. Conf. Distributed Comput. Syst. , Minneapolis, MN, USA, 2011,pp. 268–277.

R. H. Glitho, “Cloud-based multimedia conferencing: Business model, research agenda, state-of-the-art,” in Proc. 13th IEEE Conf. Commerce Enterprise Comput. , Sep. 2011, pp. 226–230.

C. Gadea, B. Solomon, B. Ionescu, and D. Ionescu, “A collaborative cloud-based multimedia sharing platform for social networking environments,” in Proc. 20th Int. Conf. Comput. Commun. Netw. , Maui, HI, USA, 2011, pp. 1–6.

B. Yang, F. Tan, and Y. S. Dai, “Performance evaluation of cloud service considering fault recovery,” J. Supercomput., pp. 1–19, Feb. 2011.

D. Koavchev, Y. Cao, and R. Klamma, “Mobile multimedia cloud computing and the web,” in Proc. Workshop Multimedia Web , Graz, Austria, 2011,

W. Zhu, C. Luo, J. Wang, and S. Li, “Multimedia cloud computing,” IEEE Signal Process. Mag. , vol. 28, no. 3, pp. 59–69, May 2011.

W. Hui, H. Zhao, C. Lin, and Y. Yang, “Effective load balancing for cloud-based multimedia system,” China, 2011, pp. 165–168.

J. Chen, S. Wuy, Y. T. Larosa, P. Yang, and Y. Li, “IMS cloud computing architecture for high-quality multimedia applications,” in Proc. IEEE Int. Wireless Commun. Mobile Comput. Conf. , Istanbul, Turkey, Jul. 2011, pp. 1463–1468.

A. Andrzejak, D. Kondo, and Y. Sangho, “Decision model for cloud computing under SLA constraints,” in Proc. 18th Annu. IEEE/ACM Int. Symp. Modeling, Anal. Simulation Comput. Telecommun. Syst. , Miami Beach, FL, USA, Aug. 2010, pp. 257–266.

W.W. Zhang, Y.G. and D.P. Wu, “Energy-Efficient Scheduling Policy for Collaborative Execution in Mobile Cloud Computing,” in INFOCOM, Mini Conf., 2013.

W.W. Zhang, Y.G. Wen, Z.Z. Chen and A. Khisti, “QoE-Driven Cache Management for HTTP Adaptive Bit Rate Streaming over Wireless Networks,” in IEEE Transactions on Multimedia, November 2012.

J. Li, M. Qiu, Z. Ming, G. Quan, X. Qin, and Z. Gu, “Online Optimization for Scheduling Preemptable tasks on IaaS Cloud systems,”in Journal of Parallel and Distributed Computing (JPDC), vol.72, no.5, pp.666-677, 2012.

P. Calyam, M. Sridharan, Y. Xu , K. Zhu , A. Berryman, R. Patali, and A. Venkataraman, “Enabling Performance Intelligence for Application Adaptation in the Future Internet,” in Journal of Communication and Networks, vol. 13, no. 6, pp. 591–601, 2011.

Z. Huang, C. Mei, L. E. Li, and T. Woo, “CloudStream : Delivering High-Quality Streaming Videos through A Cloud-based SVC Proxy,” in IEEE INFOCOM, 2011.

N. Davies, “The Case for VM-Based Cloudlets in Mobile Computing,” in IEEE Pervasive Computing, vol. 8, no. 4, pp. 14–23, 2009. [22] B. Aggarwal, N. Spring, and A. Schulman, “Stratus: Energy-Efficient Mobile Communication using Cloud Support,” in ACM SIGCOMM DEMO, 2010.

Z. Wu, N. Chu, and P. Su, “Improving cloud service reliability—A system accounting approach,” in Proc. IEEE 9th Int. Conf. Services Comput., Honolulu, Hawaii, Jun. 2012, pp. 90–97.

J. Gao, P. Pattabhiraman, X. Bai, and W. T. Tsai, “SaaS performance and scalability evaluation in clouds,” in Proc. IEEE 6th Int. Symp. Service Oriented Syst. Eng., Irvine, CA, USA, Dec. 2011, pp. 61–71.

A. Gambi and G. Toffetti, “Modeling cloud performance with kriging,” in Proc. 34th Int. Conf. Software Eng., Zurich, Switzerland, 2012, pp.1439–1440.

A. Iosup, S. Ostermann, M. N. Yigitbasi, R. Prodan, T. Fahringer, and D. H. J. Epema, “Performance analysis of cloud computing services for many-tasks scientific computing,” IEEE Trans. Parallel Distributed Syst., vol. 22, no. 6, pp. 931–945, Jun. 2011


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