On the performance of multi-level time sharing policy under heavy-tailed workloads

Many existing works on multi-level time sharing policies have assumed infinitely small quanta, infinite levels or exponential service time distributions. In this paper, we investigate the performance of a multi-level time sharing policy under heavy-tailed workloads under finite levels when quanta are not infinitely small. Such a policy is consistent with those implemented on modern computer systems and these findings will enable system designers to better understand how various factors (e.g. system load, task size variability and number of levels) affect the overall performance of a given system. First, we obtain the performance metrics for a multi-level time sharing policy with finite number of levels. Second, for the case of 2 and 3 levels (queues), we show that optimal quantum multi-level time sharing policy (MLOQTP) can result in significant performance improvements over other policies under certain traffic and workload conditions. Finally, we investigate the impact of number of levels on the overall performance and propose a simple statistical regression model that can accurately estimate overall performance of a multi-level time sharing system.