Utility-based On-demand Heuristic Strategy to Grid Computing

Abstract

Grids aim at exploiting synergies that result from cooperation of autonomous distributed entities. For this cooperation to be sustainable, participants need to have economic incentive. Within service-oriented Grids, resources may be advertised and traded as services, and QoS requirement is the most important attribute. In this paper, we build on two intellectual threads: market-based approaches and the economic theory of utility to resource allocation. We consider the problem of task scheduling subject to time and budget constrains as QoS-aware joint utility function, and scheduling object is to maximize total attained utility. This scheduling problem can be shown to be NP-hard, thus we present a utility-driven heuristic scheduling algorithm (UDS) for this problem. We study the performance of UDS algorithm through a stochastic Petri net (SPN) model. In the end, the performance of model is analyzed by SPNP software package. The numerical results show that UDS can guarantee QoS for users