Framework for resource management in a grid environment

Abstract

Grid Computing heralds the dawn of a new paradigm for next-generation high performance computing. As a descendent of distributed computing, it enables selection, sharing and aggregation of geographically distributed resources for solving intricate problems of science, engineering and commerce, which have phenomenal computational needs. It offers reasonable, consistent and pervasive access to high-end computation, mainly as a result of availability of faster hardware, more sophisticated software and escalation of Internet. The principles of Grid computing focus on large-scale resource sharing in distributed systems in a flexible, secure, and coordinated fashion. Resource management forms the core of Grid computing. Resources in a Grid are often geographically distributed, heterogeneous and dynamic in nature. Resources are owned by different organizations with different usage policies, cost models, varying loads and availability patterns. The conventional resource management schemes are based on the assumption that resources are owned by a single organization and therefore, would be available exclusively. There are relatively static models that have centralized controller that manage jobs and resources accordingly. These assumptions do not hold true for a Grid environment. Therefore, in spite of a number of advances in Grid Computing, resource management persists to be a challenging, complex, yet most significant task and has been the main focus of this research work. Initially, a detailed review of the work done in the area of Grid Resource Management has been done. It analyzes, compares and reports existing approaches to Grid resource management, state of the art in Grid resource management and the challenges, that need to be addressed. A comparative analysis of middleware technologies has been done for Grid resource management and fault management mechanisms.