Optimal state-free, size-aware dispatching for heterogeneous M/G/ M / G / -type systems
We consider a cluster of heterogeneous servers, modeled as M/G/1 M / G / 1 first-come first-serve queues with different processing speeds. A dispatcher that assigns jobs to the servers takes as input only the size of the arriving job and the overall job-size distribution. This general model captures the behavior of a variety of real systems, such as web server clusters. Our goal is to identify assignment strategies that the dispatcher can perform to minimize expected completion time and waiting time. We show that there exist optimal strategies that are deterministic, fixing the server to which jobs of particular sizes are always sent. We prove that the optimal strategy for systems with identical servers assigns a non-overlapping interval range of job sizes to each server. We then prove that when server processing speeds differ, it is necessary to assign each server a distinct set of intervals of job sizes in order to minimize expected waiting or response times.
heterogeneous servers scheduling queueing systems load balancing m/g/1 m / g / 1 m/g/1 m / g / 1 m/g/1 m / g / 1 m / g / 1 parallel servers