Hybrid approach for monitoring and scheduling the job in heterogeneous system

Abstract

Main process of grid computing is Resources allocation and job scheduling. It aggregates heterogeneous resources distributed across Internet, regardless of differences between resources such as platform, hardware, software, architecture, language, and geographical location. Grid resource state monitoring cares about the running state, distribution, load, and malfunction of resources in a grid system by means of monitoring strategies. Grid resource state prediction focuses on the variation trend and running track of resources in a grid system by means of modeling and analyzing historical monitoring data. A computing grid is a complex distributed system. Embedded with the grid, its resource monitoring and prediction system is also a distributed system that dynamically processes grid resource state information. Then, we present our overall system architecture design that seamlessly integrates various cooperating components to achieve high performance. The monitoring techniques employed by such projects are partly compatible to the grid environment and, thus, fit for achieving grid resource monitoring.