Scheduling task to heterogeneous processors by modified ACO algorithm

Heterogeneous computing environment is having diverse computational requirements and utilizes a dispersed set of various high-performing machine with high-speed interlinks to perform varieties of computational applications. To meet out the demand of large and group of computational task, heterogeneous computing environment will be the best environment. The set of regular task assigned to heterogeneous processor has been a problem of determining the respective task with timing, and it is set to be NP-hard. In this research, a new optimization algorithm is proposed for scheduling and allocation. To improve the assigning and scheduling task to meet out the resource utilization and energy consumption, a local search algorithm can be used. In addition to feasible assignment solution, the algorithm can optimize the processor’s energy consumption. The optimization algorithm is simulated with Extensive Java Agent Development Framework (JADE) simulator, and its results show that the approach offers accurate, efficient, and effective method for lower energy consumption.