Memory Constrained ANT Colony System for Task Scheduling in GRID Computing

Grid computing solves the increasing need of scientific, engineering and research problems. It combinesthe geographically distributed resources to solve a computation intensive problem which cannot be solvedusing a single resource. Resource sharing requires more optimized algorithmic structure, otherwise theresponse time is increased and the resource utilization is reduced. In order to avoid such reduction in theperformance of the grid system, an optimal resource sharing algorithm is required. The ACO solves manyengineering problems and provides optimal result which includes Travelling Salesman Problem, NetworkRouting, and Scheduling. This paper proposes Load Shared Ant Colony Optimization (LSACO) whichshares the load among the available resources. The proposed method considers memory requirement as aparameter to distribute the load among Grid resources. LSACO reduces the overall response time andincreases the resource utilization and number of tasks scheduled. The proposed method has been tested fordifferent types of tasks and resources.