A Novel Context and Load-Aware Family Genetic Algorithm Based Task Scheduling in Cloud Computing

Conference paper
First Online:
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 542)

Abstract

With the advent of web technologies and efficient networking capabilities, desktop applications are increasingly getting amalgamated with the touch of cloud computing. Most of the recent developments are dominated by consumer centric market, ensuring best quality of service and hence, greater customer base, leading to the rise of peaks in the profit charts. However, certain challenges in the field of cloud need to be dealt with, before peak performance is achieved and resource scheduling is one of these. This paper aims to present a context and load aware methodology for efficient task scheduling using modified genetic algorithm known as family genetic algorithm. Based on analysis of user characteristics, user requests are fulfilled by the right type of resource. Such a classification helps attain efficient scheduling and improved load balancing and will prove advantageous for the future of the cloud. Results show that the proposed technique is efficient under various circumstances.

Keywords

Load balancing Cloud Task scheduling Workload Genetic algorithm 
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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Computer Engineering and TechnologyGuru Nanak Dev UniversityAmritsarIndia

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