Abstract

To realise the utmost idea of global collaborative resource sharing with Grid computing, the fundamental scheduling process is playing a critical role. However, scheduling in Grid computing environment is a well-known NP-complete problem. In this study, we propose a new extension of Great Deluge algorithm with an effective diversification strategy for the Grid scheduling problem. The proposed approach, namely BiGD, exploits two different decay rates (a linear and a non-linear decay rate of water level) to provide a better diversification strategy for exploring the solution space. The performance of the proposed algorithm has been evaluated and compared with the standard Great Deluge and Extended Great Deluge algorithm, through the GridSim simulation toolkit. Four different scheduling scenarios or cases which comprise different combination of task heterogeneity and resource heterogeneity are considered for the performance evaluation. Moreover, we have adapted all the algorithms to have same total number of evaluation for solution searching in order to ensure a fair comparison is established in the performance evaluation. The experimental simulation results show that the proposed algorithm is superior and able to produce good quality solutions compared to the other algorithms in all the problem instances.

Highlights

  • As new generation of information technologies and applications demand more and more computing power, Grid computing has become one of the most popular computing infrastructures to satisfy this ever-increasing demand of computing power

  • We propose a new extension of Great Deluge algorithm with bi-decay rate, which uses a linear and a non-linear decay rate of water level to efficiently guide the search in finding a better quality of solution preventing it from getting stuck in the local optima

  • Four different scheduling scenarios or cases which comprise different combination of task heterogeneity and resource heterogeneity are considered for the performance evaluation

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Summary

Introduction

As new generation of information technologies and applications demand more and more computing power, Grid computing has become one of the most popular computing infrastructures to satisfy this ever-increasing demand of computing power. The task of mapping in Grid Computing environment is very large-scale due to the enormous amount of tasks and resources that need to be considered in each mapping decision. To solve such large-scale NP-Complete problem, exact optimisation method or exhaustive search is not viable. The Great Deluge algorithm is extended with two different decay rates to provide a better diversification strategy for escaping from local optima and allowing the search process to examine wider regions of solution space.

Literature Review
Tasks which submitted to Grid scheduler are scheduled in batch mode
A processor can only process one task at a time
Objective
Results and Discussion
Conclusion
Funding Information
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