Modified Ant Colony Optimization for Workflow Scheduling in Cloud Enviornment

S.J. Mohana; Dr.M. Saroja; Dr.M. Venkatachalam

doi:10.24297/ijct.v14i10.6936

Authors

S.J. Mohana Erode Arts and Science college, Erode, India.
Dr.M. Saroja Erode Arts and Science college, Erode, India.
Dr.M. Venkatachalam Erode Arts and Science college, Erode, India.

DOI:

https://doi.org/10.24297/ijct.v14i10.6936

Keywords:

Cloud computing, workflow scheduling, ant colony optimization, modified ant colony optimization, virtual machines

Abstract

Cloud computing is a type of parallel and distributed system consisting of a collection of interconnected and virtual computers. This technological trend has enabled the realization of a new computing model called cloud computing, in which shared resources, information,software & other devices are provided according to client requirement at specific time, are provided as general utilities that can be leased and released by users through the Internet in an on-demand fashion.Cloud workflow scheduling is an NP-hard optimization problem, and many meta-heuristic algorithms have been proposed to solve it.Allocation of resources to a large number of workflows in a cloud computing environment presents more difficulty than in network computational environments.A good task scheduler should adapt its scheduling strategy to the changing environment and the types of tasks. In this work, modified ant colony optimization for cloud task scheduling is proposed. The goal of modification is to enhance the performance of the basic ant colony optimization algorithm and optimize the task execution time in view of minimizing the makespan of a given tasks set.

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