Survey of location-centric target tracking with mobile elements in wireless sensor networks

介绍目标跟踪的过程以及移动跟踪的特点;通过区分目标定位为主的方法和目标探测为主的方法,介绍定位为主的移动式目标跟踪方法(称为目标的移动式定位跟踪; )的研究现状;分析和比较不同方法的特点和应用领域,发现现有方法虽然可以提高跟踪质量、降低网络整体能耗,但是还存在一些问题。基于此,总结目标的移动; 式定位跟踪方法在方法类型、网络结构和节点模型等方面可能存在的研究热点,指出其研究和发展趋势。The basic process of target tracking and the properties of tracking; solutions with mobile elements were introduced. By distinguishing; location-centric methods and detection-centric methods, the current; research status of the location-centric target tracking methods were; reviewed. The properties and application fields of different solutions; were analyzed and compared. Although the existing solutions can; significantly improve tracking quality and reduce energy consumption of; the whole network, there are also some problems. Based on these; discoveries, some possible research hotspots of mobile solutions were; summarized in many aspects, such as method types, network architecture,; node model, and so on, indicating the future direction of research and; development.国家自然科学基金资助项目; 国家科技支撑计划项

Delay-Constrained Mobile Energy Charging in Wireless Sensor Networks

为了延长无线传感网的生存期,基于可充电的移动设备,研究设计了一种无线传感网中移动式能量补充的方法,移动节点可以在为传感器节点补充能量的同时收集数; 据.首先,通过将无线传感器网络监测区域分割为大小相同的子区域,该子区域内的节点组成一个簇;其次,以一个簇内的总能量为计算依据,设计移动节点的路径; 生成算法以确定能量高效的移动路线;最后,使用10种不同的随机网络拓扑图进行了仿真实验,以节点移动速度和时延为限制条件分别得到了对比数据.结果表明; ,本文提出的算法与NJNP( nearest-job-next with preemption)算法相比在时延相同的条件下( 800; s),生存期提升了6 000 s左右,在节点速度5 m/s条件下生存期提升了将近14 000; s.证明本文所提方法有效地提高了充电效率,延长了网络的生存期,可用于大规模的无线传感器网络.In order to prolong the lifetime of wireless sensor networks by using; energy-rechargeable mobile devices,this paper designs a mobile energy; replenishment method wherein a mobile element gathers data and recharges; sensors simultaneously. Firstly,the whole sensor network is divided into; several sub-regions equally and the sensors in each sub-region are; formed into a cluster. Secondly, considering the energy in a whole; cluster,the mobility path is designed to find the energy-efficient; mobile trace of the mobile element. Finally,in the simulation; experiment,we used ten different random network topologies to show the; comparisons with extensive simulation experiments under different; velocities and deadlines. The results indicate that the proposed; algorithm increases lifetime by approximately 6 000 s compared with; Nearest-Job-Next with Pre-emption( NJNP) under the deadline of 800 s.; Moreover,the proposed algorithm increases lifetime by approximately 14; 000 s compared with NJNP at velocity of 5 m/s. Thus,the proposed; algorithm can improve recharging efficiency and prolong the lifetime of; wireless sensor networks,which can be used in large-scale sensor; networks.国家自然科学基金资助项目; 福建省高等学校杰出青年科研人才培育计划资助项

Survey on Coverage Control with Mobile Elements in Wireless Sensor Networks

在无线传感器网络中,节点能量限制、硬件以及通信链路故障等问题,造成网络空洞的产生且影响了网络的正常运作,因此如何确保网络覆盖率成为传感器网络中需; 要解决的重要问题.近年来,通过引入移动节点来进行覆盖控制,提高传感器网络的覆盖率成为一个新的研究趋势.本文通过充分调研利用移动节点进行网络覆盖控; 制的方法,并对其进行了分类和比较,归纳了移动式网络覆盖的各种方法的特点,分析这些方法的性能和适用范围,总结存在的主要问题,并指出未来的研究方向.Due to the existence problems of energy depletion,hardware failure and; communication link failure and so on,which causes network holes and; affects the normal network operation. The insurance of coverage becomes; an urgent issue in wireless sensor networks. In recent years, a new; research trend is to utilize mobile nodes for coverage control, which; increases the coverage of wireless sensor networks. In this paper, we; have a comprehensive investigation about the current major topology; control methods with mobile nodes,and summarize the characteristics of; mobile topology control methods via classification and comparison of; these methods. Finally,we analyze the performances and the application; scopes of these methods, summarize the main problems,and point out the; future research directions.国家自然科学基金重点项目; 国家科技支撑计划项目; 国家自然科学基金项目; 福建省科技计划重点项

Object tracking sensor networks in smart cities: Taxonomy, architecture, applications, research challenges and future directions

The development of pervasive communication devices and the emergence of the Internet of Things (IoT) have acted as an essential part in the feasibility of smart city initiatives. Wireless sensor network (WSN) as a key enabling technology in IoT offers the potential for cities to get smatter. WSNs gained tremendous attention during the recent years because of their rising number of applications that enables remote monitoring and tracking in smart cities. One of the most exciting applications of WSNs in smart cities is detection, monitoring, and tracking which is referred to as object tracking sensor networks (OTSN). The adaptation of OTSN into urban cities brought new exciting challenges for reaching the goal of future smart cities. Such challenges focus primarily on problems related to active monitoring and tracking in smart cities. In this paper, we present the essential characteristics of OTSN, monitoring and tracking application used with the content of smart city. Moreover, we discussed the taxonomy of OTSN along with analysis and comparison. Furthermore, research challenges are investigated concerning energy reservation, object detection, object speed, accuracy in tracking, sensor node collaboration, data aggregation and object recovery position estimation. This review can serve as a benchmark for researchers for future development of smart cities in the context of OTSN. Lastly, we provide future research direction

Following targets for mobile tracking in wireless sensor networks

Traditional tracking solutions in wireless sensor networks based on fixed sensors have several critical problems. First, due to the mobility of targets, a lot of sensors have to keep being active to track targets in all potential directions, which causes excessive energy consumption. Second, when there are holes in the deployment area, targets may fail to be detected when moving into holes. Third, when targets stay at certain positions for a long time, sensors surrounding them have to suffer heavier work pressure than do others, which leads to a bottleneck for the entire network. To solve these problems, a few mobile sensors are introduced to follow targets directly for tracking because the energy capacity of mobile sensors is less constrained and they can detect targets closely with high tracking quality. Based on a realistic detection model, a solution of scheduling mobile sensors and fixed sensors for target tracking is proposed. Moreover, the movement path of mobile sensors has a provable performance bound compared to the optimal solution. Results of extensive simulations show that mobile sensors can improve tracking quality even if holes exist in the area and can reduce energy consumption of sensors effectively

Following targets for mobile tracking in wireless sensor networks

202402 bcchAccepted ManuscriptOthersNational Natural Science Foundation (NSF) of China; Natural Science Foundation of Fujian Province of China; Young and Middle-aged Teacher in Science and Technology Research of Huaqiao UniversityPublishedGreen (AAM