A Hybrid Approach for Energy-Efficient Task Scheduling in Cloud

Task scheduling is a big problem in the cloud computing. As large number of users simultaneously request for the resources, the tasks must be allocated to resources rapidly and in an optimized manner. Energy consumption by data centers worldwide has increased tremendously. This leads to focus on developing eco-friendly and energy-efficient scheduling algorithms. A lot of techniques for energy-efficient task scheduling have already been proposed, yet there is a lot of room for improvements. We are presenting a hybrid of Genetic Algorithm and Artificial Bee Colony-based approach along with DVFS to achieve energy-efficient task scheduling. Empirical analysis of the proposed approach proves its better performance over Modified Genetic Algorithm with respect to makespan and energy consumption.