  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.
