Agent Based Processing of Global Evaluation Function

Load balancing across a networked environment is a monotonous job. Moreover, if the job to be distributed is a constraint satisfying one, the distribution of load demands core intelligence. This paper proposes parallel processing through Global Evaluation Function by means of randomly initialized agents for solving Constraint Satisfaction Problems. A potential issue about the number of agents in a machine under the invocation of distribution is discussed here for securing the maximum benefit from Global Evaluation and parallel processing. The proposed system is compared with typical solution that shows an exclusive outcome supporting the nobility of parallel implementation of Global Evaluation Function with certain number of agents in each invoked machine.