Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/9112
標題: 使用M/M/R/K排隊系統分析雲端服務帶有中途退出之利潤最大化研究
Profit Maximization Analysis in Cloud Computing Using M/M/R/K Queuing System with Impatient Customers
作者: 江依儒
Chiang, Yi-Ju
關鍵字: 服務水平協議
service level agreements
M/M/R/K排隊系統
系統阻擋率
中途退出率
M/M/R/K queuing system
blocking probability
reneging probability
loss probability.
出版社: 電機工程學系所
引用: [1] The NIST Definition of Cloud Computing, http://www.nist.gov/itl/cloud/upload/cloud-def-v15.pdf. [2] M. Armbrust, A. Fox, R. Griffith, et al., “Above the clouds: a Berkeley view of cloud computing,” Technical Report No UCB/EECS-2009-28, University of California at Berkeley, USA, 2009. [3] H. Khazaei, J. Misic, and V. B. Misic, “Performance Analysis of Cloud Computing Centers Using M/G/m/m+r Queuing Systems,” IEEE Transactions on Parallel and Distributed Systems, vol. 23, no. 5, pages 936-943, 2012. [4] K. Wang, N. Li, and Z. Jiang, “Queueing System with Impatient Customers: A Review,” IEEE International Conference on Service Operations and Logistics and Informatics (SOLI), pages 82-87, 2010. [5] A. I. Pazgal, S. Radas, “Comparison of customer balking and reneging behavior to queueing theory predictions: An experimental study,” Computers & Operations Research, Volume 35, Issue 8, pages 2537-2548, 2008. [6] A. P. Ghosh, A. P. Weerasinghe, “Optimal buffer size and dynamic rate control for a queueing system with impatient customers in heavy traffic,” Stochastic Processes and their Applications, Volume 120, Issue 11, pages 2103-2141, 2010. [7] D. Doran, L. Lipsky and S. Thompson, “Cost-based Optimization of Buffer Size in M/G/1/N Systems Under Different Service-time Distributions,” Proceedings of 9th IEEE Network Computing and Applications (NCA), pages 28-35, 2010. [8] Y. C. Lee, C. Wang, A. Y. Zomaya, and B. B. Zhou, “Profit-driven scheduling for cloud services with data access awareness,” Journal of Parallel and Distributed Computing, vol. 72, pages 591-601, 2012. [9] B. Yang, F. Tan, Y. Dai, and S. Guo, “Performance Evaluation of Cloud Service Considering Fault Recovery,” Proc. First Int’l Conf. Cloud Computing (CloudCom ’09), pages 571-576, 2009. [10] Introduction to Data Center Infrastructure Management, http://www.raritan.com/resources/white-papers/dcim/Introduction-to-Data-Center-Infrastructure-Management.pdf, 2010. [11] Best Practices Guide for Energy-Efficient Data Center Design, http://www1.eere.energy.gov/femp/pdfs/eedatacenterbestpractices.pdf, 2011. [12] D. Gross, J. F. Shortle, J. M. Thompson and C. M. Harris. Fundamentals of Queuing Theory (Fourth edition), A John Wiley & Sons, Inc., New York, 2008. [13] P. Afeche and H. Mendelson, “Pricing and Priority Auctions in Queueing Systems with a Generalized Delay Cost Structure,” MANAGEMENT SCIENCE, Vol. 50, No. 7, pages 869–882, 2004. [14] P. Guo, P. Zipkin, “Analysis and Comparison of Queues with Different Levels of Delay Information,” MANAGEMENT SCIENCE Vol. 53, No. 6, pages 962–970, 2007. [15] J. Ou, B.M. Rao, “Benefits of providing amenities to impatient waiting customers,” Computers & Operations Research, Vol. 30, Issue 14, pages 2211-2225, 2003. [16] D. Durkee, “Why cloud computing will never be free,” Communications of the ACM, vol. 53, no. 5, pages 62-69, 2010. [17] A. P. Chandrakasan, S. Sheng, and R. W. Brodersen, “Low power CMOS digital design,” IEEE Journal on Solid-State Circuits, vol. 27, no. 4, pages 473-484, 1992. [18] B. Zhai, D. Blaauw, D. Sylvester, and K. Flautner, “Theoretical and practical limits of dynamic voltage scaling,” Proceedings of the 41st Design Automation Conference, pages 868-873, 2004. [19] CPU power dissipation, http://en.wikipedia.org/wiki/CPU_power_dissipation. [20] Central processing unit, http://en.wikipedia.org/wiki/Central_processing_unit. [21] CMOS, http://en.wikipedia.org/wiki/CMOS. [22] J. Cao, K. Hwang, L. Li, and A. Y. Zomaya, “Optimal multiserver configuration for profit maximization in cloud computing,” IEEE Transactions on Parallel and Distributed Systems, Vol. 24 , Issue: 6, pages 1087 - 1096, 2013. [23] J. Baliga, R.W. A. Ayre, K. Hinton and R. S. Tucker, “Green Cloud Computing: Balancing Energy in Processing, Storage, and Transport,” Proceedings of The IEEE, vol. 99, no. 1, pages 149-167, 2011. [24] Y. C. Lee ‧ A. Y. Zomaya, “Energy efficient utilization of resources in cloud computing systems,” Journal of Supercomputing, 2012.
摘要: 隨著大型雲端計算服務平台的不斷發展,資源如何配置才能降低營運成本的負擔,同時保證滿足服務水平協議SLA成為服務供應者面臨的主要挑戰。在本文中,用M/M/R/K有限等待緩衝區的排隊模型來模擬多伺服器配置的雲端服務系統,同時考慮到使用者中途退出的行為。在系統性能和營運成本的分析下建立一個單位時間的預估利潤函數,其中的服務率和緩衝區的大小是兩個主要的系統配置決策參數。 系統阻擋率和使用者中途退出率是兩個主要的預估損失。由於系統丟失機率是直接受到這兩值的影響,所以SLA服務性能保證專注在於丟失率,約束條件是需小於一個保證值:丟失率≤ x,其中x是一個最大臨界值。在本文中對於兩個主要的問題進行了分析和解決。第一個是對於降低系統擁塞度和節省運作成本的衝突關係採用折衷的方法來做調整。第二是我們的決策方法可以根據最後到達的工作量、系統配置成本和SLA性能保證範圍內,提供一個明確決定來控制服務率和緩衝區空間。讓滿足SLA的性能保證擁有最高的優先權,其次是獲得最大的利潤。最後我們的系統和M/M/R系統做比較,證明能夠達到利潤增長和明顯的服務性能改善。
Cloud computing realize utility computing paradigm by offering shared resources through Internet-based. However, how resources provisioning can reduce the burden of operational cost and simultaneously meet service level agreements (SLAs) have become the main challenge for cloud providers. We model a cloud server farm with finite buffer as an M/M/R/K queuing system. Since no customers want to endure long waiting time, impatient customers are considered in our designed service system. In order to properly control system blocking rates and avoid excessive reneging rate, SLA is specified by guaranteeing: loss probability ≤ x, where x is a maximum threshold value. Three important issues are solved in this paper. First, tradeoff is conducted to resolve the conflicts between system performances and cost savings. Second, a profit function which includes system congestion costs and operational costs per unit time is developed. Blocking loss and reneging loss are also considered in revenue estimation. Satisfying SLA has the highest priority, followed by profit maximization. Finally, simulation results show that the optimal resources provisioning of service rate and buffer space can be obtained to maximize profit.
URI: http://hdl.handle.net/11455/9112
其他識別: U0005-1607201316481300
文章連結: http://www.airitilibrary.com/Publication/alDetailedMesh1?DocID=U0005-1607201316481300
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