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Meta-heuristic based framework for workflow load balancing in cloud environment - 2019

Research Area:  Cloud Computing

Abstract:

Cloud services are based on datacenter which provides resources on demand with higher capacity, lowest response time and improved resource utilization. The data center comprises of physical hosts which are effectively utilized in the form of Virtual Machines. The task scheduling problem is the mapping of tasks to suitable resources (VMs) as required and it is NP-hard problem. Further, the scheduling algorithms are followed by load balancing techniques for efficient utilization of VMs. In this paper a framework for Load balancing in Cloud Environment has been proposed and implemented for overflow and underflow VM identification. Two metaheuristics and one heuristic have been used in the proposed framework to achieve effective and efficient utilization of VMs in cloud environment. Further, the performance of the proposed framework has been analysed on the basis of makespan and cost metrics which are computed while executing scientific workflow tasks.

Author(s) Name:  Amanpreet Kaur, Bikrampal Kaur & Dheerendra Singh

Journal name:  International Journal of Information Technology

Conferrence name:  

Publisher name:  Springer

DOI:  10.1007/s41870-018-0231-z

Volume Information:  volume 11, pages 119–125 (2019)