Cost-efficient Multi-tasking in Coverage-aware Mobile Crowd Sensing

Abstract

In Mobile Crowd Sensing (MCS), task assignment and user selection to minimize the total incentive cost is a crucial issue that has received a lot of attention recently. Previous works studied incentive techniques for single-task assignment schemes, but multi-task assignment schemes are a more practical consideration as MCS applications are becoming increasingly popular. In this paper, we aim at minimizing the total incentive cost for all task publishers while considering related variables such as coverage, workload and sensor availability. Specifically, we motivate and propose a cost-efficient incentive mechanism that encourages multi-tasking versus a single-task assignment scenario. We present a novel metric called Combined Satisfaction Factor (CSF) that measures the total amount of satisfaction for both task publishers and task workers. We conduct simulations experiments to test our proposed scheme and show that our scheme improves the cost-efficiency for task creators by 13% and significantly increases the satisfaction levels in the system.