An Efficient Fault Tolerant Job Scheduling and Load Balancing in Grid Computing

Abstract

In Grid environment, the two main techniques that are most suitable to cope with the dynamic nature of the grid are load balancing and job replication. In Load balancing algorithm juxtaposes is considered the strong point is neighbour based and cluster based methods. We propose a genetic algorithm for job scheduling to address the heterogeneity of fault-tolerance mechanisms problem in a computational grid. We assume that the system supports four kinds fault-tolerance mechanisms, including the job retry, the job migration without check pointing, the job migration with check pointing, and the job replication mechanisms. Because each fault-tolerance mechanism has different requirements for the gene encoding, we also propose a new chromosome encoding approach to integrate the four kinds of mechanisms in a chromosome. The risky nature of the grid environment is also taken into account in the algorithm. The risk relationship between jobs and nodes are defined by the security demand and the trust level.