Bragged Regression Tree Algorithm for Dynamic Distribution and Scheduling of Jobs

In the past few years, Grid computing came up as next generation computing platform which is a combination of heterogeneous computing resources combined by a network across dynamic and geographically separated organizations. So, it provides the perfect computing environment to solve large-scale computational demands. As the Grid computing demands are still increasing from day to day due to rise in large number of complex jobs worldwide. So, the jobs may take much longer time to complete due to poor distribution of batches or groups of jobs to inappropriate CPU’s. Therefore there is need to develop an efficient dynamic job scheduling algorithm that would assign jobs to appropriate CPU’s dynamically. The main problem which dealt in the paper is, how to distribute the jobs when the payload, importance, urgency, flow time etc. dynamically keeps on changing as the grid expands or is flooded with number of job requests from different machines within the grid. In this paper, we present a scheduling strategy which takes the advantage of decision tree algorithm to take dynamic decision based on the current scenarios and which automatically incorporates factor analysis for considering the distribution of jobs.