A paper entitled ‘Queuing Algorithm for Effective Target Coverage in Mobile Crowd Sensing' has been published recently in IEEE Internet of Things Journal. This paper is a joint work of co-authorship from 4 universities in 4 countries (West Virginia University, Deakin University, University of Ottawa), representing a good output of international collaboration and geographical coverage. The publication can be accessedhere.

Abstract—In recent years, various researches have been conducted in order to find ways to cover a target or groups of targets with priority based target coverage and sensor deployment mechanisms taking the front seats. However, with these researches, effective target coverage has been a recurrent issue due to various factors like conflict between sensors and excessive waiting time for targets to be covered. In this paper, we proposed an algorithm based on queuing theory in tandem with mobile crowd sensing to tackle these issues. To do this, first, we develop some models which are based on the birth-and-death mechanism (one of the tools in queuing theory) to determine how long a target has to wait, the mean busy period of sensors and mean idle period of sensors. While developing these models, we considered cases where there exist a single sensor and n-sensors in the system. Based on these models, we developed the required algorithm. The simulation result shows that as the number of sensors increase relative to the number of targets, an average time before a target gets discovered is 0.2 seconds and sensor utilization decreasing towards zero as the number of sensors increases.

最近,USLab在IEEE期刊Internet of Things Journal发表了论文“Queuing Algorithm for Effective Target Coverage in Mobile Crowd Sensing”。基于排队理论,该论文在群智感知场景中提出了一种针对有效地监测某区域内多个目标所需要的感知节点的部署机制算法。本文是USLab与来自另外3个国家3所高校的同行合作发表,体现了良好的国际合作和地域覆盖。全文可以在此处获取。