Master/slave computing on the Grid

Resource selection is fundamental to the performance of master/slave applications. In this paper, we address the problem of promoting performance for distributed master/slave applications targeted to distributed, heterogeneous "Grid" resources. We present a work-rate-based model of master/slave application performance which utilizes both system and application characteristics to select potentially performance-efficient hosts for both the master and slave processes. Using a Grid allocation strategy based on this performance model, we demonstrate a performance improvement over other selection options for a representative set of master/slave applications in both simulated and actual Grid environments.