Security-Aware Distributed Job Scheduling in Cloud Computing Systems: A Game-Theoretic Cellular Automata-Based Approach

We consider the problem of security-aware scheduling and load balancing in Cloud Computing (CC) systems. This optimization problem we replace by a game-theoretic approach where players tend to achieve a solution by reaching a Nash equilibrium. We propose a fully distributed algorithm based on applying Iterated Spatial Prisoner's Dilemma (ISPD) game and a phenomenon of collective behavior of players participating in the game. Brokers representing users participate in the game to fulfill their own three criteria: the execution time of the submitted tasks, their execution cost and the level of provided Quality of Service (QoS). We experimentally show that in the process of the game a solution is found which provides an optimal resource utilization while users meet their applications' performance and security requirements with minimum expenditure and overhead.