Fault Tolerant – Optimal Resource Allocator for Cloud
Khiruparaj T. P.1, Abishek Madhu. V2, Ponsy R. K. Sathia Bhama3
1Khiruparaj T.P., Department of Computer Technology, Madras Institute of Technology – Anna University, Chennai, India.
2Abishek Madhu, Department of Computer Technology, Madras Institute of Technology, Anna University, Chennai, India.
3Ponsy R.K. Sathia Bhama*, Associate Professor in the Department of Computer Technology, Madras Institute of Technology, Anna University, Chennai, India.

Manuscript received on November 22, 2019. | Revised Manuscript received on November 28, 2019. | Manuscript published on November 30, 2019. | PP: 2565-2571 | Volume-8 Issue-4, November 2019. | Retrieval Number: D7190118419/2019©BEIESP | DOI: 10.35940/ijrte.D7190.118419

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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Cloud Computing is mainly attracted by people for its unlimited storage space and worldwide accessibility from anywhere and anytime. The data that is stored in the cloud has to be retrieved in a faster manner as well as without any faults. Content Delivery Networks dominates Cyberspace traffic heavily due to its increasing demand. Resource allocation plays a vital role in determining the performance of the cloud. Over allocation leads to wastage which can be used for instances that are running short of resources. This work proposes an optimal resource allocation through Genetic algorithm. They help in increasing the download speed which in turn would be helpful in controlling traffic to greater extent. Recently cloud downloading Services have been emerged, in which cloud storage hoards the user interested content and updates the cloud cache. This process takes place in two modes, server mode and the helper mode. The proposed Resource Allocation Policy can well support the server mode of processing by the way it can increment the download speed with dynamic load balancing and fault tolerance.
Keywords: Cloud Computing, File Downloading, Genetic Algorithm, Peer-To-Peer, Resource Optimization.
Scope of the Article: Cloud Computing.