High performance load balancing schemes for cluster based secure web server
Proceedings of the International Conference and Workshop on Emerging Trends in Technology
Joint admission control and resource allocation in virtualized servers
Journal of Parallel and Distributed Computing
Journal of Systems and Software
Dynamic resource provisioning for interactive workflow applications on cloud computing platform
MTPP'10 Proceedings of the Second Russia-Taiwan conference on Methods and tools of parallel programming multicomputers
Dual time-scale distributed capacity allocation and load redirect algorithms for cloud systems
Journal of Parallel and Distributed Computing
Algorithms for Web service selection with static and dynamic requirements
Service Oriented Computing and Applications
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With increasing richness in features such as personalization of content, web applications are becoming increasingly complex and hence compute intensive. Traditional approaches for improving performance of static content web sites have been based on the assumption that static content such as images are network intensive. However, these methods are not applicable to the dynamic content applications which are more compute intensive than static content. This paper proposes a suite of algorithms which jointly optimize the performance of dynamic content applications by reducing the client access times while also minimizing the resource utilization. A server migration algorithm allocates servers on-demand within a cluster such that the client access times are not affected even under sudden overload conditions. Further, a server selection mechanism enables statistical multiplexing of resources across clusters by redirecting requests away from overloaded clusters. We also propose a cluster decision algorithm which decides whether to migrate in additional servers at the local cluster or redirect requests remotely under different workload conditions. Through a combination of analytical modeling, trace-driven simulation over traces from large e-commerce sites and testbed implementation, we explore the performance savings achieved by the proposed algorithms.