A "folk" solution to decrease Nash Equilibrium inefficiency for a job scheduling game

In a distributed system as a Grid, one of the most important targets is to optimize load balancing or thread throughput. As matter of fact in such distributed systems, jobs concur to access shared and distributed resources. For this reason, we modeled a scheduler as a job scheduling game, where multiple jobs concur to use multiple processing cores as players of this game. For each job needs to choose a single core to process it. The payoff of each job is to minimize his job completion time, maximizing the total system throughput. In order to solve this game problem, the integration of Nash Equilibrium and MiniMax solution has been tested in a new algorithm. So the main purpose of this research is to validate the decrease of Nash Equilibrium inefficiency for this proposed distributed model. Experimental tests have focused on the evaluation of different algorithm behavior in order to measure its efficiency.