The Impact of Quanta on the Performance of Multi-level Time Sharing Policy under Heavy-tailed Workloads

Jayasinghe, M., Tari, Z. and Zeephongsekul, P.

    Recent research indicates that modern computer workloads (e.g. processing time of web requests) follow heavy-tailed distributions. In a heavy-tailed distribution there are a large number of small tasks and a small number of large tasks. The rationale for using a multi-level time sharing policy is that it can minimise both waiting time and slowdown of tasks that require relatively small service requirements. This in turn will improve the overall performance of the system. Using a 2-level system (policy), we investigate the effect of quanta on the overall performance of a multi-level time sharing policy under a range of workloads and task size variabilities. We measure the performance using slowdown and flow time. First, we show that for most workloads and task size variabilities there exists a unique set of quanta ('optimal' set of quanta) that would result in the best performance. Second, we investigate the performance degradation in one metric under the optimal parameters of other metric. Through an extensive numerical analysis, we find that under high system loads and task size variabilities using the optimal set of quanta corresponding to overall expected slowdown can result in the overall expected flow time to deteriorate significantly. Finally we show that a 3-level system with the optimal set of quanta outperforms a 2-level system with the optimal set of quanta for all the scenarios considered.
Cite as: Jayasinghe, M., Tari, Z. and Zeephongsekul, P. (2009). The Impact of Quanta on the Performance of Multi-level Time Sharing Policy under Heavy-tailed Workloads. In Proc. Thirty-Second Australasian Computer Science Conference (ACSC 2009), Wellington, New Zealand. CRPIT, 91. Mans, B., Ed. ACS. 83-91.
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