Mobility and Battery Power Prediction Based Job Scheduling in Mobile Grid Environment

Over the past decade, the grid has emerged as an attractive platform to tackle various large-scale problems, especially in science and engineering. Recent advances in mobile communications and computing, and strong interest of the scientific community in the Grid have led to research into the Mobile Grid. However, mobile devices often have limited resources in terms of CPU, storage, battery power, and communication bandwidth. One primary issue associated with the efficient and effective utilization of mobile resources in a mobile grid is scheduling. Mobile grid scheduling involves a number of challenging issues, mainly due to the dynamic nature of the mobile grid. In this paper, a task scheduling algorithm is proposed based on the dynamic availability prediction of mobile resources. A just-in-time approach is employed in this paper where availability prediction of a mobile resource is evaluated as tasks are submitted, allowing the system to consider run-time parameters (mobility and battery power) prior to execution. The evaluation study employs a number of experiments with various simulation settings. The simulation results points to the efficacy of the proposed work.