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Genetic Algorithm-Based Optimal Resource Trust Line Prediction in Cloud Computing

S. Mercy

Department of Information Science and Engineering, Bangalore Institute of Technology, Bangalore, Karnataka, India

E-mail Address: mercy.isaac.abraham

Corresponding author.

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M. Jaiganesh

Department of Information Technology, Karpagam College of Engineering, Coimbatore, Tamil Nadu, India

E-mail Address: jaidevlingam@gmail.com

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R. Nagaraja

Department of Information Science and Engineering, Bangalore Institute of Technology, Bangalore, Karnataka, India

E-mail Address: prof.rnagaraja@yahoo.com

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, and

G. Sudha

Department of Electrical and Electronics Engineering, Bangalore Institute of Technology, Bangalore, Karnataka, India

E-mail Address: profgsudha@gmail.com

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https://doi.org/10.1142/S146902682341002XCited by:2 (Source: Crossref)

This article is part of the issue:

Special Issue on Smart Fuzzy Optimization for Decision-Making in Uncertain Environments
Guest Editors: Er Meng Joo, Danilo Pelusi and Shiping Wen

Abstract

A cloud computing signifies a novel computing paradigm that endorses reactive delivery of resources and services. A distinctive cloud service of such data center deploys over many computing nodes requesting services from the data centers. The organization of resources and trustworthiness of client is a hot topic of research in cloud computing. One of the major threats in cloud computing is unauthorized access of hardware and their resources. To conquer the issue, this novel work proposes an Optimal Resource Trust line prediction using Genetic Algorithm (GAORTL). The main aim of the work is to find the allocated optimal resource utilization of clients through an evolutionary algorithm. Implementation is evaluated to prove the benefit of the algorithm. Subsequently, we perform a comprehensive investigation that the proposed GAORTL delivers a better prediction of trustworthiness in variety of client sizes for a big scale batch of occurrences.

Keywords:

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