On Stochastic Performance and Cost-Aware Optimal Capacity Planning of Unreliable Infrastructure-as-a-Service Cloud

• Published in: Algorithms and Architectures for Parallel Processing Vol. 10048; pp. 644 - 657
• Main Authors: Li, Weiling, Wu, Lei, Xia, Yunni, Wang, Yuandou, Guo, Kunyin, Luo, Xin, Lin, Mingwei, Zheng, Wanbo
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2016; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Algorithms & data structures; IaaS cloud; Optimal capacity planning; Simulated annealing
• ISBN: 9783319495828; 3319495828
• ISSN: 0302-9743; 1611-3349
• DOI: 10.1007/978-3-319-49583-5_50

Performance evaluation of cloud data-centers has drawn considerable attention from academy and industry. In this study, we present an analytical approach to the performance analysis of Infrastructure-as-a-Service cloud data-centers with unreliable task executions and resubmissions of unsuccessful tasks. Several performance metrics are considered and analyzed under variable load intensities, failure frequencies, multiplexing abilities, and service intensities. We also conduct a case study based on a real-world cloud data-center and employ a confidence interval check to validate the correctness of the proposed model. For the performance optimization and optimal capacity planning purposes, we are also interested in knowing the minimized expected response time subject to the constraint of request rejection rate, hardware cost in terms of the cost of physical machines and the request buffer. We show that the optimization problem can be numerically solved through a simulated-annealing-based algorithm.