Task Scheduling Using an Adaptive PSO Algorithm in Cloud Computing Environment

Now-a-days energy planners are aiming to increase the use of renewable energy sources and nuclear to meet the electricity generation. But till now coal-based power plants are the major source of electricity generation. The problem of task scheduling is one of the most important steps in taking advantage of the cloud computing environment. Various experiments show that although it is almost impossible to have an optimal solution, it seems that there is a more optimal solution using heuristic algorithms. This work compares three heuristic approaches to scheduling cloud environment tasks. These approaches are the PSO algorithm, the ACO, and the adaptive PSO algorithm for efficient task scheduling. The goal of all three of these algorithms is to generate an optimal schedule to minimize task completion time.