Performance Analysis for Heterogeneous Cloud Servers Using Queueing Theory

© 2020 IEEE. Personal use of this material is permitted. Permissíon from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertisíng or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.[EN] In this article, we consider the problem of selecting appropriate heterogeneous servers in cloud centers for stochastically arriving requests in order to obtain an optimal tradeoff between the expected response time and power consumption. Heterogeneous servers with uncertain setup times are far more common than homogenous ones. The heterogeneity of servers and stochastic requests pose great challenges in relation to the tradeoff between the two conflicting objectives. Using the Markov decision process, the expected response time of requests is analyzed in terms of a given number of available candidate servers. For a given system availability, a binary search method is presented to determine the number of servers selected from the candidates. An iterative improvement method is proposed to determine the best servers to select for the considered objectives. After evaluating the performance of the system parameters on the performance of algorithms using the analysis of variance, the proposed algorithm and three of its variants are compared over a large number of random and real instances. The results indicate that proposed algorithm is much more effective than the other four algorithms within acceptable CPU times.This work is supported by the National Key Research and Development Program of China Grant No. 2017YFB1400801, the National Natural Science Foundation of China Grant Nos. 61572127, 61872077, 61832004 and Collaborative Innovation Center of Wireless Communications Technology. Rub~en Ruiz is partly supported by the Spanish Ministry of Science, Innovation, and Universities, under the project "OPTEP-Port Terminal Operations Optimization" (No. RTI2018-094940-BI00) financed with FEDER funds.Wang, S.; Li, X.; Ruiz García, R. (2020). Performance Analysis for Heterogeneous Cloud Servers Using Queueing Theory. IEEE Transactions on Computers. 69(4):563-576. https://doi.org/10.1109/TC.2019.295650556357669