Abstract
This paper considers task scheduling in solarpowered Internet of things (IoT) networks where devices are capable of sharing energy wirelessly. Our aim is to minimize the completion time of all tasks. We outline a novel mixed integer linear program (MILP) to schedule tasks and determine whether devices share their harvested energy via radio frequency (RF) in each time slot. The MILP considers the coupling between the energy level at devices across time slots. It also considers the dependency of tasks, whereby each task must be executed on a given set of devices in a specific order. Further, we propose a heuristic algorithm called minimum time first with energy sharing (MinTime-ES) for large scale networks. Our results show that with energy sharing, MILP and MinTime-ES achieve 28.86 and 7.83% reduction in task completion time as compared to competing algorithms that do not consider energy sharing between devices.
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