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An efficient load balancing strategy based on mapreduce for public cloud

Published:22 March 2017Publication History

ABSTRACT

Cloud computing has emerged as the most promising technology concept within several structures regardless of their industries. However, the exponential growth experienced by the Cloud has significantly complicated the administration of Cloud platforms. One aspect of the sustainability of Cloud development remains the performance of services supplied by Cloud providers. Through this paper, we propose to tackle the particular feature of performance optimization within the Cloud model by introducing a load balancing architecture based on the MapReduce concept. Indeed, the geographic extent of physical resources which are implemented in different datacenters of the Cloud is at the same time strength in terms of fault tolerance and availability for critical resources, but also a weakness in terms of management of the load balancing of the system. Indeed, the proposed architecture will take advantage from the MapReduce principles to handle the massive number of available resources in order to find out the most appropriate load balancer regarding the requirements of users' requests. The proposed architecture aims to improve both the response time and the fault tolerance within the Cloud.

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    • Published in

      cover image ACM Other conferences
      ICC '17: Proceedings of the Second International Conference on Internet of things, Data and Cloud Computing
      March 2017
      1349 pages
      ISBN:9781450347747
      DOI:10.1145/3018896

      Copyright © 2017 ACM

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      New York, NY, United States

      Publication History

      • Published: 22 March 2017

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      ICC '17 Paper Acceptance Rate213of590submissions,36%Overall Acceptance Rate213of590submissions,36%

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