Robust sequential resource allocation in heterogeneous distributed systems with random compute node failures

The problem of finding efficient workload distribution techniques is becoming increasingly important today for heterogeneous distributed systems where the availability of compute nodes may change spontaneously over time. Therefore, the resource-allocation policy must be designed to be robust with respect to absence and re-emergence of compute nodes so that the performance of the system is maximized. Such a policy is developed in this work, and its performance is evaluated on a model of a dedicated system composed of a limited set of heterogeneous Web servers. Assuming that each HTML request results in a rdquorewardrdquo if completed before its hard deadline, the goal is to maximize a cumulative reward obtained in the system. A failure rate for each server is set relatively high to simulate its operation under harsh conditions. The results demonstrate that the proposed approach based on the concepts of the Derman-Lieberman-Ross theorem outperforms other policies compared in our experiments for inconsistent, processor-consistent, and task-processor-consistent types of heterogeneity.