A Novel Context and Load-Aware Family Genetic Algorithm Based Task Scheduling in Cloud Computing
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
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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 algorithm
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Cloud
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Task scheduling
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Workload
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Genetic
1 Introduction Distributed computing was developed with the idea of enhancing the processing power of computers with visible benefits, making it evolve into the grid, cluster and cloud computing. Delivering computing resources as a utility became a very K. Kaur (✉) ⋅ N. Kaur ⋅ K. Kaur Department of Computer Engineering and Technology, Guru Nanak Dev University, Amritsar 143005, India e-mail: [email protected] N. Kaur e-mail: [email protected] K. Kaur e-mail: [email protected] © Springer Nature Singapore Pte Ltd. 2018 S.C. Satapathy et al. (eds.), Data Engineering and Intelligent Computing, Advances in Intelligent Systems and Computing 542, DOI 10.1007/978-981-10-3223-3_51
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welcomed idea all over the world, leading to the success of cloud [1]. Several authors have tried to define cloud, according to its characteristics, utility paradigm, structure or by comparing it with grid. In simple words, the cloud can be defined as a large pool of resources available to the users on pay per use model where scalability, reliability, security, heterogeneity, usability and other Qos parameters are taken care of. This makes cloud computing an enormously future oriented paradigm [2]. Talking about the structure and modeling of cloud, the layered architecture basically represents three main classes viz infrastructure, platform and software as a service. Virtualization augments this model by providing a logical interface to access cloud resources and makes it possible for cloud providers to modify this platform further into XaaS (everything as a service) [3]. Multi-tenancy, shared resource pooling, geo-distribution, self-organizing, dynamism in resource provisioning are some of salient features of cloud that ensure great response from its users. While all other architectures like grid, utility computing or other distributed computing environments, cloud computing with its fabulous architecture allows users with all kinds of ne
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