Design and analysis of a dynamic scheduling strategy with resource estimation for large-scale grid systems

In this paper, we present a resource conscious dynamic scheduling strategy for handling large volume computationally intensive loads in a grid system involving multiple sources and sinks/processing nodes. We consider a "pull-based" strategy, wherein the processing nodes request load from the sources. We employ the Incremental Balancing Strategy (IBS) algorithm proposed in the literature and propose a buffer estimation strategy to derive optimal load distribution. We consider nontime critical loads that arrive at arbitrary times with time varying buffer availability at sinks and utilize buffer reclamation techniques so as to schedule the loads. We demonstrate detailed workings of the proposed algorithm with illustrative examples using real-life parameters derived from STAR experiments in BNL for scheduling large volume loads.