LOAD BALANCING AND JOB MIGRATION IN GRIND COMPUTING

Abstract

Grid computing is applying the resources of many computers in a network to a single problem at the same time - usually to a scientific or technical problem that requires a great number of computer processing cycles or access to large amounts of data. Grid computing appears to be a promising trend because its ability to make more cost-effective use of a given amount of computer resources, as a way to solve problems that can't be approached without an enormous amount of computing power, and because it suggests that the resources of many computers can be cooperatively and perhaps synergistically harnessed and managed as a collaboration toward a common objective. Grid Computing has progressed a lot, yet, there are some areas of concern, like resource management, resource scheduling, load balancing and security over which, research is still in progress. Load balancing is a great challenge in dynamic and heterogeneous environment like Grids. Load balancing is a technique to enhance resources, utilizing parallelism, improve throughput, and to cut response time through an appropriate distribution of the applications. The main goal of load balancing is to provide a distributed, low cost, scheme that balances the load across all the processors. An effective and efficient load balancing algorithm is required to balance the load in Grid environment, which is a tedious task due to basic nature of Grid environment. Focus of this thesis is to analyze all the existing load balancing algorithms and to do a comparative study. After considering all pros and cons of all the existing algorithms, a new load balancing algorithm has been proposed based on all positive aspects of existing algorithms.