Performance comparison of heuristic algorithms for task scheduling in IaaS cloud computing environment.

Syed Hamid Hussain Madni,Mohammed Abdullahi,Shafi’I Muhammad Abdulhamid,Muhammad Shafie Abd Latiff,Mohammed Joda Usman,Kim-Kwang Raymond Choo

doi:10.1371/journal.pone.0176321

Abstract

Cloud computing infrastructure is suitable for meeting computational needs of large task sizes. Optimal scheduling of tasks in cloud computing environment has been proved to be an NP-complete problem, hence the need for the application of heuristic methods. Several heuristic algorithms have been developed and used in addressing this problem, but choosing the appropriate algorithm for solving task assignment problem of a particular nature is difficult since the methods are developed under different assumptions. Therefore, six rule based heuristic algorithms are implemented and used to schedule autonomous tasks in homogeneous and heterogeneous environments with the aim of comparing their performance in terms of cost, degree of imbalance, makespan and throughput. First Come First Serve (FCFS), Minimum Completion Time (MCT), Minimum Execution Time (MET), Max-min, Min-min and Sufferage are the heuristic algorithms considered for the performance comparison and analysis of task scheduling in cloud computing.

Highlights

Cloud computing has become one of the most attractive fields in both ICT (Information and Communication Technology) trade and academic research
We present the performance comparison of heuristic algorithms for task scheduling in IaaS cloud computing system. These algorithms are executed with the help of CloudSim simulator in homogeneous and heterogeneous environments with and without using workload traces. These algorithms are compared with each other based on some parameters like cost, degree of imbalance, makespan and throughput
For the heuristics studied in this paper, overall Min-min algorithm performs better than other heuristics, while Max-min and sufferage algorithm give good results and Minimum Execution Time (MET) algorithm always shows better performance in achieving the degree of imbalance for optimal task scheduling in IaaS cloud computing

Summary

Introduction

Cloud computing has become one of the most attractive fields in both ICT (Information and Communication Technology) trade and academic research. Some of the functions and services of cloud computing environment include advanced security, geographical distribution of large scale data, resilient computing, virtualization, web infrastructure, Web 2.0 and other developing technologies. Users can access provision, process, store and network important computer resources, operating systems, virtual desktops, web services, development platforms and databases. It uses specific applications as services offered by cloud computing providers as a “utility” on “pay as you go”. Many benefits of the cloud computing environment include cost saving, energy efficiency, flexibility, high accessibility, rapid implementation and scalability [1,2,3].

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