A Pure Nash Equilibrium-Based Game Theoretical Method for Data Replication across Multiple Servers

This paper proposes a non-cooperative game based technique to replicate data objects across a distributed system of multiple servers in order to reduce user perceived Web access delays. In the proposed technique computational agents represent servers and compete with each other to optimize the performance of their servers. The optimality of a non-cooperative game is typically described by Nash equilibrium, which is based on spontaneous and non-deterministic strategies. However, Nash equilibrium may or may not guarantee system-wide performance. Furthermore, there can be multiple Nash equilibria, making it difficult to decide which one is the best. In contrast, the proposed technique uses the notion of pure Nash equilibrium, which if achieved, guarantees stable optimal performance. In the proposed technique, agents use deterministic strategies that work in conjunction with their self-interested nature but ensure system-wide performance enhancement. In general, the existence of a pure Nash equilibrium is hard to achieve, but we prove the existence of such equilibrium in the proposed technique. The proposed technique is also experimentally compared against some well-known conventional replica allocation methods, such as branch and bound, greedy, and genetic algorithms.