Comparison and analysis of greedy energy-efficient scheduling algorithms for computational grids
A computational grid is a distributed computational network, enabled with software that allows cooperation and the sharing of resources. The energy consumption of these large-scale distributed systems is an important problem. As our society becomes more technologically advanced, the size of these computational grids and energy consumption continue to increase. In this paper, we study the problem of optimizing energy consumption and makespan by focusing on different techniques to schedule the tasks to the computational grid. A computational grid is simulated using a wide range of task heterogeneity and size variety. The heuristics are used with the simulated computational grid and the results are compared extensively against each other.
We present a novel approach to the synchronization problem. It is a well-known fact that a problem of finding minimal (or: the shortest) synchronizing word (MSW) for a given synchronizing automaton is NP-complete. In this paper we present the genetic algorithm which tries, for a given automaton, to find possibly short word that synchronizes it. We use a modified version of a classical simple genetic algorithm (SGA).