Load balancing strategies for Grid computing

Grid computing is the combination of computer resources from multiple administrative domains for a common goal. Grid computing (or the use of a computational grid) is applying the resources of many computers in a network to a single problem at the same time - usually to solve a scientific or technical problem that requires a great number of computer processing cycles or access to large amounts of data. One of the main strategies of Grid computing is to use middleware to divide and apportion pieces of a program among several computers, sometimes up to many thousands. Grid computing involves computation in a distributed fashion, which may also involve the aggregation of large-scale cluster computing based systems. The size of a Grid may vary from small - confined to a network of computer workstations within a corporation, for example - to being large, public collaboration across many companies and networks. "The notion of a confined grid may also be known as intra-nodes cooperation whilst the notion of a larger, wider grid may thus refer to inter-nodes cooperation". Since the spectrum of grid computing is too much broad it is very much important to balance the load among the various nodes of the network. Various load balancing algorithms were developed assuming homogenous set of nodes linked with homogenous and fast networks. In this paper we studies the various load balancing strategies that control the load of the entire system.