Uslab Published a Paper Recently in IEEE Internet of Things Journal (USLab近期在IEEE期刊Internet of Things Journal发表学术论文) [2017-04-15]

发布时间:2017-04-15
 
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 accessed here.
 
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。
 
  摘要:近年来,针对有效的基于优先级的目标覆盖和监测传感器的部署机制,一直是研究热点,其中传感器之间的协调监测和目标被监测等待时间问题研究较少。在本文中,我们提出了一种基于排队论和多个移动传感器(如多个智能手机携带者)感知的算法解决这些问题。首先,我们利用出生-死亡模型(排队论的工具之一)提出了对应算法以确定目标等待时间、传感器的平均繁忙期和平均空闲期。我们分成了只有单一传感器和有多个移动传感器的情形,分别进行推导。仿真结果表明,随着传感器数量相对于目标数量的增加,目标被发现(监测)的平均时间是0.2秒,并且随着传感器的数目增加而利用率降低到零。