An efficient overload control strategy in cloud

Authors:
Xiling Sun;Jiajie Xu;Zhiming Ding;Xu Gao;Kuien Liu
Affiliations:
NFS, Institute of Software, Chinese Academy of Sciences, Beijing, China;NFS, Institute of Software, Chinese Academy of Sciences, Beijing, China;NFS, Institute of Software, Chinese Academy of Sciences, Beijing, China;NFS, Institute of Software, Chinese Academy of Sciences, Beijing, China;NFS, Institute of Software, Chinese Academy of Sciences, Beijing, China
Venue:
APWeb'12 Proceedings of the 14th international conference on Web Technologies and Applications
Year:
2012

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Abstract

In cloud, service performances are expected to meet various QoS requirements stably, and a great challenge for achieving this comes from the great workload fluctuations in stateful systems. So far, few previous works have endeavored for handling overload caused by such fluctuations. In this paper, we propose an efficient overload control strategy to solve this problem. Crucial server status information is indexed by R-tree to provide global view for data movement. Based on index, a two-step filtering approach is introduced to eliminate irrational server candidates. A server selection algorithm considering workload patterns is presented afterwards to acquire load-balancing effects. Extensive experiments are conducted to evaluate the performance of our strategy.