A Game Theory-Based Pricing Strategy to Support Single/Multiclass Job Allocation Schemes for Bandwidth-Constrained Distributed Computing Systems

Today´s distributed computing systems incorporate different types of nodes with varied bandwidth constraints which should be considered while designing cost-optimal job allocation schemes for better system performance. In this paper, we propose a fair pricing strategy for job allocation in bandwidth-constrained distributed systems. The strategy formulates an incomplete information, alternating-offers bargaining game on two variables, such as price per unit resource and percentage of bandwidth allocated, for both single and multiclass jobs at each node. We present a cost-optimal job allocation scheme for single-class jobs that involve communication delay and, hence, the link bandwidth. For fast and adaptive allocation of multiclass jobs, we describe three efficient heuristics and compare them under different network scenarios. The results show that the proposed algorithms are comparable to existing job allocation schemes in terms of the expected system response time over all jobs