Abstract:
This projects considers delay requirements when scheduling virtual machines (VMs) in a queueing cloud computing system with stochastic arrivals of heterogeneous jobs. In such a cloud computing system, delay-optimal VM scheduling is a multi-resource multi-class problem to minimize average job completion time, which is often NP-hard.
A queueing model that buffers VM jobs of the same type in one virtual queue solves this problem. The queueing model divides VM scheduling into two parallel low-complexity algorithms: intra-queue buffering and inter-queue scheduling.
A min-min best fit (MM-BF) policy schedules jobs in different queues to minimize system resources, while a shortest-job-first (SJF) policy buffers job requests in each queue in ascending order by job length. SJF-QMW minimizes VM job queue lengths using Lyapunov drift to avoid job starvation for long-duration jobs in SJF-MMBF. Simulations show that SJF-MMBF and SJF-QMW have low average job completion time and high job hosting ratio.
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