Multi-dimensional resource allocation strategy for large- scale computational grid systems

Abstract

In this thesis, we propose a novel distributed resource-scheduling algorithm capable of handling multiple resource requirements for jobs that arrive in a Grid Computing Environment. Our algorithm, referred to as Multi-Dimension Resource Scheduling (MRS) algorithm, takes into account both site capabilities and resource requirements of jobs. The main objective of the algorithm is to obtain a minimal execution schedule through efficient management of available Grid resources. We introduce the concept of a n-dimensional virtual map and resource potential. Based on the proposed model, we conduct rigorous simulation experiments with real-life workload traces to quantify the performance. Our combined consideration of job and resource characteristics is shown to render high-performance with respect to above-mentioned metrics in the environment.