A hybrid heuristic resource allocation model for computational grid for optimal energy usage. (2018)

• Record Type: Journal Article
• Authors: Kaushik, Achal; Vidyarthi, Deo Prakash
• Is Part Of: International journal of grid and utility computing. Volume 9:Number 1(2018)
• Page Start: 51
• Page End: 74
• Publication Date: 2018
• Subjects: computational grid -- green energy -- resource allocation -- genetic algorithm -- MST -- minimum spanning tree -- QoS -- quality of service; Electronic data processing -- Distributed processing -- Periodicals; Electronic commerce -- Management -- Computer programs -- Periodicals; 004.605
• Languages: English
• ISSNs: 1741-847X

Abstract

Computational grid helps in faster execution of compute intensive jobs. The resource allocation for the job execution in computational grid demands a lot of characteristic parameters to be optimised but in the process the green aspect is ignored. Reducing the energy consumption in computational grid is a major recent issue among researchers. The conventional systems, which offer energy efficient scheduling strategies, ignore other quality of service parameters while scheduling the jobs. The proposed work tries to optimise the energy for resource allocation and at the same time makes no compromise on other related characteristic parameters. A hybrid model, that uses genetic algorithm and graph theory concept has been proposed for this purpose. In this model, an energy saving mechanism is implemented using a dynamic threshold method followed by genetic algorithm to further consolidate the saving. Eventually, a graph theory concept of Minimum Spanning Tree (MST) is applied. The performance of the proposed model has been studied by its simulation. The result reveals the benefits achieved with the proposed model for optimal energy with resource allocation in the grid.