Performance-based middleware for Grid computing

This paper describes a stateful service-oriented middleware infrastructure for the management of scientific tasks running on multi-domain heterogeneous distributed architectures. Allocating scientific workload across multiple administrative boundaries is a key issue in Grid computing and as a result a number of supporting services including match-making, scheduling and staging have been developed. Each of these services allows the scientist to utilize the available resources, although a sustainable level of service in such shared environments cannot always be guaranteed. A performance-based middleware infrastructure is described in which prediction data for each scientific task are calculated, stored and published through a Globus-based performance information service. Distributing these data allows additional performance-based middleware services to be built, two of which are described in this paper: an intra-domain predictive co-scheduler and a multi-domain workload steering system. These additional facilities significantly improve the ability of the system to meet task deadlines, as well as enhancing inter-domain load-balancing and system-wide resource utilization