Random Walk based ACO Load Balancing Algorithm for Cloud Computing Environment

	International Journal of P2P Network Trends and Technology (IJPTT)
	© 2018 by IJPTT Journal
	Volume-8 Issue-6
	Year of Publication : 2018
	Authors : Nishu Rana, Dr.Pardeep Kumar

Citation

MLA Style: Nishu Rana, Dr.Pardeep Kumar "Random Walk based ACO Load Balancing Algorithm for Cloud Computing Environment" International Journal of P2P Network Trends and Technology 8.6 (2018): 8-15.

APA Style:Nishu Rana, Dr.Pardeep Kumar, (2018). Random Walk based ACO Load Balancing Algorithm for Cloud Computing Environment. International Journal of P2P Network Trends and Technology, 8(6), 8-15.

Abstract

In a few years, Cloud computing has got unstoppable growth. As the Cloud Computing is developed day by day the Cloud providers requires optimization of various services to achieve a high level of security, availability and responsiveness. The virtual machines are migrated lively to produce efficient result to realize load balancing as well as to optimize utilization of resources. Now a day, the most challenging for service providers is to maintain reliability and elasticity and lesser the Makespan (MS) and better the resource utilization (RU). That is the reason Cloud Service providers requires a dynamic load balancing algorithm. Dynamic Load Balancing (DLB) algorithms are those that deceases the Makespan (MS) while increases the resource utilization. For such problems, Metaheuristic Optimization Approaches have been successfully proved to produce near-optimal solutions with fair time. In order to improve the cloud computing utilization, Random Walk Ant Colony Optimization (RWACO) is proposed. The proposed RWACO algorithm improves pheromone factors, Makespan as well as for better Resource Utilization (RU) characterized by the existing algorithm. Results of simulation are conducted in the CloudSim and these results indicate that RWACO is superior to the conventional ACO.

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Keywords
Cloud Computing, Load Balancer, Ant Colony Optimization, Levy Flight’s, Make-span, Resource-utilizations.