Grid Computing: The Case Study Of Grid Computing

1. INTRODUCTION
1.1 BRIEF INTRODUCTION
Grid computing is defining the combination of computer resources from many numbers of administrative domains to reach the existing goal. The grids have heterogeneity and geographic disreputability in its resources. Grids can solve grand challenge applications using the Computer Modeling, Simulation and Analysis. Grids can be available in the form of distributed computing and differs from the other architectures like as a cluster. Grid computing can overcome the limitations such as the conventional shared computing mood and to become a principal trend in the distributed computing system. Grid core service is the Centre of grid computing which can take the charge of entire grid system in order to give definite grid system with its work effectiveness. The grid core service is an important part in the grid computing and the task scheduling strategy is the part of grid core service. The grid resources are required more number of tasks and the system can optimizes the resource through scheduling the tasks reasonably.
Grid Computing is an ultimate framework to meet the improving methods of computational demands for the new generation. To meet the improving methods of the power computation and geographic distribution of resources need to be logically coupled

Figure-1.3 illustrates the functional block diagram of a Genetic Algorithm. It is assumed that the potential solution to the problem may be represented through a set of parameters. These parameters are joined together and to form a string of values (known as the chromosome). The particular values in the genes represent are called its alleles .In the chromosome the position of the gene is same as its locus. Encoding the issues deal with representing the solution in the chromosome and unfortunately no other technique works best for all