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Queueing Network-based Optimisation Techniques for Workload Allocation in Clusters of Computers
Shanghai, China September 15-September 18
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/SCC.2004.1358008Services Computing, 2004 IEEE Interna ...
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Ligang He, University of Warwick, UK
Stephen A. Jarvis, University of Warwick, UK
David Bacigalupo, University of Warwick, UK
Daniel P. Spooner, University of Warwick, UK
Xinuo Chen, University of Warwick, UK
Graham R. Nudd, University of Warwick, UK
This paper addresses workload allocation techniques for clusters of computers. The workload in question is homogenous or heterogeneous. Homogeneous workload contains only QoS-demanding jobs (QDJ) or non-QoS jobs (NQJ) while heterogeneous workload is a mix of QDJs and NQJs. The processing platform used is a single cluster or multiple clusters of computers. Two workload allocation strategies (called ORT and OMR) are developed for homogeneous workloads by establishing and numerically solving optimisation equation sets. The ORT strategy achieves the Optimised mean Response Time for homogeneous NQJ workload; while the OMR strategy achieves the Optimised mean Miss Rate for homogeneous QDJ workload. Based on ORT and OMR, a heterogeneous workload allocation strategy is developed to dynamically partition the clusters into two parts. Each part is managed by ORT or OMR to exclusively process NQJs or QDJs. The judicial partitioning achieves an optimised comprehensive performance, which combines the mean response time and the mean miss rate. The effectiveness of these workload allocation techniques is demonstrated through queueing-theoretical analysis as well as through experimental studies. These techniques can be applied to e-business workload management to improve the distribution of different types of requests in clusters of servers.
Citation:
Ligang He, Stephen A. Jarvis, David Bacigalupo, Daniel P. Spooner, Xinuo Chen, Graham R. Nudd, "Queueing Network-based Optimisation Techniques for Workload Allocation in Clusters of Computers," scc, pp.207-216, Services Computing, 2004 IEEE International Conference on (SCC'04), 2004
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