Resource Provisioning and Scheduling In Clouds Based On Timeframe Using Particle Swarm Optimization

N.Rupavathy*, M.Mahil**, M.S.Mumtaj Zareena***
* P.G. Scholar, Department of CSE, Govt.College of Engineering, Tirunelveli, India.
** Assistant Professor, Department of CSE, Govt.College of Engineering, Tirunelveli, India
*** P.G. Scholar, Department of CSE, Govt.College of Engineering, Tirunelveli, India.
Periodicity:September - November'2014
DOI : https://doi.org/10.26634/jit.3.4.3093

Abstract

The initiation of resource provisioning in cloud computing for workflow scheduling. Most demanding issues in Clouds is Workflow Scheduling. However, Clouds are different from Grids in few ways: on-demand resource provisioning, homogeneous networks and the pay-as-you-go pricing model. We are proposing resource provisioning and scheduling strategy for scientific workflows using meta-heuristic optimization algorithm known as Particle Swarm Optimization. It aims is to minimize the overall execution cost while meeting timeframe constraints in various scientific workflows of different sizes. The results have been evaluated using Cloudsim with different QoS parameters which are user defined. The approach performs better than the genetic and ant colony optimization algorithms.

Keywords

Cloud Computing, Resource Provisioning, Resource Scheduling, Particle Swarm Optimization, Workflow

How to Cite this Article?

Rupavathy. N, Mahil. M and Zareena. M. S. M (2014). Resource Provisioning And Scheduling In Clouds Based On Timeframe Using Particle Swarm Optimization. i-manager’s Journal on Information Technology, 3(4), 32-38. https://doi.org/10.26634/jit.3.4.3093

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