A novel fault-tolerant task scheduling algorithm for computational grids

Abstract

A computational grid is a hardware and software infrastructure that provides consistent, dependable, pervasive and expensive access to high-end computational capabilities in a multi-institutional virtual organization. Computational grids provide computing power needed for execution of tasks. Scheduling the task in computing grid is an important problem. To select and assign the best resources for task, we need a good scheduling algorithm in grids. As grids typically consist of strongly varying and geographically distributed resources, choosing a fault-tolerant computational resource is an important issue. The main scheduling strategy of most fault-tolerant scheduling algorithms depends on the response time and fault indicator when selecting a resource to execute a task. In this paper, a scheduling algorithm is proposed to select the resource, which depends on a new factor called Scheduling Success indicator (SSI). This factor consists of the response time, success rate and the predicted Experience of grid resources. Whenever a grid scheduler has tasks to schedule on grid resources, it uses the Scheduling Success indicator to generate the scheduling decisions. The main scheduling strategy of the Fault-tolerant algorithm is to select resources that have lowest tendency to fail and having more experience in task execution. Extensive experiment simulations are conducted to quantify the performance of the proposed algorithm on GridSim. GridSim is a Java based discrete-event Grid simulation toolkit. Experiments have shown that the proposed algorithm can considerably improve grid performance in terms of throughput, failure tendency and worth.