Certain Improveme
Certain
Improvements in Optimization Techniques for Grid Scheduling
N. Krishnamoorthy1 and
Dr. R. Asokan2
1. Assistant Professor (SG), Department of CSE,
Kongu Engineering College, Perundurai, Erode-638052,
2. Principal, Kongunadu College of Engineering and
Technology, Tholurpatti, Thottiam-621215, INDIA
Abstract: Grid
computing is a computing framework based on large-scale resource sharing to run
grid enabled applications. The grid system’s efficiency and quality of service
depends upon core functions such as resources discovery and scheduling. The
system attempts to optimize scheduling to enhance system performance and also
aims to use resources efficiently. This work proposes implementation of a
hybrid optimization algorithm based on Memetic and Fish School optimization
module, for optimal grid scheduling in a network grid. The proposed Memetic -
Fish Swarm Optimization (MFSO) scheme incorporates local search techniques in
the standard Fish Swarm Optimization algorithm, resulting in an efficient and
effective optimization method. The proposed approach aims to dynamically create
an optimal schedule to finish jobs within minimum time duration.
[N. Krishnamoorthy and R. Asokan. Certain
Improvements in Optimization Techniques for Grid Scheduling. Life Sci J2013;10(7s):568-572].
(ISSN: 1097-8135). http://www.lifesciencesite.com. 89
Keywords: Grid;
Resource Selection; Grid Scheduling; Memetic optimization; Fish Swarm
Optimization (FSO).
