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).