Scheduling Independent Tasks on Grid Computing Systems by Differential Evolution

Grid Computing aims to allow unified access to data, computing power, sensors and other resources through a single virtual laboratory. In this paper, we present Differential Evolution algorithm based on schedulers for efficiently allocating jobs to resources in a grid computing system. Scheduling is a key problem in emergent computational systems, such as Grid and P2P, in order to benefit from the large computing capacity of such systems. The general problem of optimally mapping tasks to machines in a heterogeneous computing suite has been shown to be NP-complete. Experimental results show that our algorithm improves the performance of static instances compared to the results of other algorithms reported in the literature.

Keywords: Grid computing, Heuristics, Differential Evolution, Makespan

^*Corresponding author: E-mail: kuchaki@mail.uk.ac.ir