Optimising static workload allocation in multiclusters

Abstract

Summary form only given. Workload allocation and job dispatching are two fundamental components in static job scheduling for distributed systems. We address the static workload allocation techniques for two types of job stream in multicluster systems, namely, nonreal-time job streams and soft-real-time job streams, which request different qualities of service. Two workload allocation strategies (called ORT and OMR) are developed by establishing and numerically solving two optimisation equation sets. The ORT strategy achieves the optimised mean response time for the nonreal-time job stream; while the OMR strategy can gain the optimised mean miss rate for the soft-real-time job stream over multiple clusters (these strategies can also be applied in a single cluster system). The effectiveness of both strategies is demonstrated through theoretical analysis. The proposed workload allocation schemes are combined with two job dispatching strategies (weighted random and weighted round-robin) to generate new static job scheduling algorithms for multicluster environments. These algorithms are evaluated through extensive experimental studies and the results show that compared with static approaches without the optimisation techniques, the proposed workload allocation schemes can significantly improve the performance of static job scheduling in multiclusters, in terms of both the mean response time (for the nonreal-time jobs) and the mean miss rate (for soft-real-time jobs).