An Optimized Cluster-Based Heterogeneous Earliest Finish Time Algorithm for Task Scheduling in Mobile Grid

In a mobile grid environment, fix and mobile devices are used to compute the tasks based on the requirement of users. However, still, task scheduling is the major challenge in the mobile grid. For task scheduling, many traditional scheduling algorithms have been presented by the researchers. Among them, Heterogeneous Earliest Finish Time (HEFT) scheduling algorithm outputs the best results. Nevertheless, the communication overhead of this algorithm is to be reduced. Thus, in this paper, we present an optimized Cluster-based HEFT (CHEFT) algorithm. Using the proposed algorithm, tasks and resources in the grid are grouped into clusters. Besides, using Pigeon-Inspired Optimization (PIO) algorithm, the clustered tasks are scheduled to the suitable clustered resources. Results of this approach show that the PIO-CHEFT-based task scheduling outperforms HEFT, Min–Min and Max–Min algorithms with respect to makespan, throughput, execution time and energy consumption.