Load Balancing Mechanisms in Amazon Web Services using Meta Heuristic Rules
Ramya Rajamanickam1, T. Hemalatha2, S. Puspalatha3, M. Buvana4
1Ramya Rajamanickam, PG Scholar, Department of CSE, PSNA CET, Dindigul (Tamil Nadu), India.
2T. Hemalatha, Professor, Department of CSE, PSNA CET, Dindigul (Tamil Nadu), India.
3S. Puspalatha, Professor, Department of CSE, PSNA CET, Dindigul (Tamil Nadu), India.
4M. Buvana, Professor, Department of CSE, PSNA CET, Dindigul (Tamil Nadu), India.
Manuscript received on 21 October 2019 | Revised Manuscript received on 25 October 2019 | Manuscript Published on 02 November 2019 | PP: 4071-4075 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B15950982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1595.0982S1119
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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 defined as the resource that can be delivered or accessed by the local host from the remote server via the internet. Cloud providers typically use a “pay-as-you-go” model. The evolution of cloud computing has led to the evolution of modern environment due to abundance and advancement of computing and communication infrastructure. During user request, and system response generation, an amount load will be assigned in the cloud computing, where it may be over or under load. Due to heavy load, power consumption and energy management problems are created, and it makes system failure and lead data loss. Though, an efficient load balancing method is compulsory to overcome all mentioned problems. The objective of this work is to develop a metaheuristic load balancing algorithm to migrate multi-server for load balancing and machine learning techniques is used to increase the cloud resource utilization and minimize the make-span time of the task. Using an unsupervised machine learning technique, it is possible to predict the correct response time and waiting time of the servers by getting the prior knowledge about the virtual machines and its clusters. And this work involves to calculate the accuracy rate of the Round-Robin load balancing algorithm and then compared it with a proposed algorithm. By this work, the response time and waiting time can be minimized and also it increases the resource utilization and minimize the make- span time of the task.
Keywords: Cloud Computing, Load Balancing, Amazon Web Service Cloud Platform, Meta Heuristics Approach, Ant Colony optimization Algorithm.
Scope of the Article: Web Technologies