Energy-aware scheduling of distributed systems using cellular automata

In today's world of large distributed systems, the need for energy efficiency of individual components is complemented by the need for energy awareness of the complete system. Hence, energy-aware scheduling of tasks on systems has become very important. Our work addresses the problem of finding an energy-aware schedule for a given system which also satisfies the precedence constraints between tasks to be performed by the system. We present a method which uses cellular automata to find a near-optimal schedule for the system. The rules for cellular automata are learned using a genetic algorithm. Though the work presented in this paper is not limited to scheduling in computing environments only, the work is validated with a sample simulation on distributed computing systems, and tested with some standard program graphs.