Responsive Multi-objective Load Balancing Transformation Using Particle Swarm Optimization in Cloud Environment

Authors

  • VG. Ravindhren Lecturer (SG), Seshasayee Institute of Technology, Tiruchirappalli. Tamil Nadu Affilated to Directorate of Technical Education, Chennai
  • S. Ravimaran Software System Group Lab, Chennai, M.A.M. College of Engineering, Tiruchirappalli, Tamil Nadu.India

DOI:

https://doi.org/10.24297/jac.v12i15.4787

Keywords:

Cloud Computing, Resource Management, responsive scheduling, dynamic scheduling, Cloud optimization.

Abstract

Cloud computing is an emerging computing paradigm with a large collection of heterogeneous autonomous systems with flexible computational architecture which provides the customers with computing resources as a service over a network on their demand. A multi-objective nature is inherent in cloud resource scheduling, as the objectives of cloud providers, cloud users, and other stakeholders can be independent. Resource allocation among multiple clients has to be ensured as per service level agreements. Several techniques have been invented and tested by research community for generation of optimal schedules in cloud computing. To accomplish these goals and achieve high performance, it is important to design and develop a Responsive multi-objective load balancing Transformation algorithm (RMOLBT) based on abstraction in multi cloud environment. It is most challenging to schedule the tasks along with satisfying the user’s Quality of Service requirements. This paper proposes a  wide variety of task scheduling and resource utilization using Particle swarm Optimization (PSO) in cloud environment. The result obtained by RMOLBT was simulated by an open source cloudsim configured with test case specification. Finally, the results  demonstrate the suitability of the proposed scheme that will increase throughput, reduce waiting time, reduction in missed process considerably and balances load among the physical machines in a Data centre in multi cloud environment.

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Author Biography

S. Ravimaran, Software System Group Lab, Chennai, M.A.M. College of Engineering, Tiruchirappalli, Tamil Nadu.India

Department of Computer Science and Engineering
Affiliated to Anna University,

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Published

2016-08-01

How to Cite

Ravindhren, V., & Ravimaran, S. (2016). Responsive Multi-objective Load Balancing Transformation Using Particle Swarm Optimization in Cloud Environment. JOURNAL OF ADVANCES IN CHEMISTRY, 12(15), 4816–4825. https://doi.org/10.24297/jac.v12i15.4787

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Articles