Mobile object tracking in wireless sensor networks (2022)


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Computer Communications

Volume 30, Issue 8,

8 June 2007

, Pages 1811-1825


Wireless sensor network is an emerging technology that enables remote monitoring objects and environment. This paper proposes a protocol to track a mobile object in a sensor network dynamically. The previous researches almost focus on how to track object accurately and they do not consider the query for mobile sources. Additionally, they need not report the tracking information to user. The work is concentrated on mobile user how to query target tracks and obtain the target position effectively. The mobile user can obtain the tracking object position without broadcast query. The user is moving and approaching the target when he/she knows the target’s position. Wireless sensor networks can assist user to detect target as well as keep the movement information of the target. Sensor nodes establish face structure to track the designated target and keep target tracks. The source follows the tracks to approaching target. To chase the object quick and maintain an accurate tracking route, the sensors cooperate together to shorten the route between target and source dynamically. A source can quickly approach a target along a shortened route. Finally, we compare the proposed scheme with three flooding-based query methods. By the simulation results, the proposed protocol has better performance than that of flooding-based query methods.

(Video) Object Tracking in Wireless Sensor Network


Recent advances in wireless communications and electronics have enabled the development of low-cost, low-power, multifunctional sensor nodes which are small in size and communicate un-tethered in short distances. These tiny sensor nodes have sensing, data processing, and communicating components capabilities. A wireless sensor network (WSN) is composed of a large number of sensor nodes and deployed either inside the phenomenon or very close to it. Wireless sensor networks are expected serve as a key infrastructure for a broad range of applications including precision agriculture, surveillance, intelligent highway systems, emergent disaster response and recovery. One of the important application issues for sensor networks is utilized to track mobile object. In such scenarios, the sensor networks may be deployed for military (tracking enemy vehicles, detecting illegal border crossings) and civilian purposes (tracking the movement of wild animals in wildlife protection). To track an object accurately, two or more of sensors are required to sense the object simultaneously [10]. The cooperation is an important issue for object tracking. However, the activated sensors need to consume power because of communication, sensing, or other factors. We would like to select the fewest essential number of sensors dedicated for the task and at the same time other sensors stay in the sleep state. During the tracking, a large number of sensors are involved in cooperation. Such object tracking sensor network provides significant research opportunities in terms of energy management. To simultaneously satisfy the requirements of saving power and improving overall efficiency, large scale coordination and other management operations are needed.

In previous object tracking sensor networks, the sensors are assumed activating. But this assumption causes that sensors in WSN consume too much energy. This is because that a lot of sensors are assigned to detect the moving object and transmit control data at the same time. Hence, we can utilize Collaborative Signal and Information Processing (CSIP) to reduce the energy consumption. For the kind of techniques, CSIP has been proposed in [3], [12], [24], [31]. In general, the object tracking protocols are classified into cluster-based and non-cluster-based protocols in WSNs. In cluster-based protocols [7], [8], [25], [30], a non-cluster sensor node detected an object and then it forwards an information to its cluster head. Next, the cluster head collects and propagates the information to a sink. This approach reduces the required communication bandwidth and energy consumption. Therefore, WSNs can prolong lifetime. In non-cluster-based protocols, there is not any node to serve as cluster head in WSNs. When a sensor detects an object, it records the object information in its local memory. A user issues a request to WSNs when he/she wants to know the location of tracked object. If a sensor has the information of the tracked object, it replies the information to the user. Kung et al. [21] and Lin et al. [23] assume that a logical structure of connecting sensors exists in WSNs. They build a hierarchical structure that allows the system to handle a large number of tracked objects. In addition, Tseng et al. [26] proposed a novel protocol based on the mobile agent. Once a new object is detected, a mobile agent will be initiated to track the roaming path of object. The mobile agent will choose and stay in a sensor that is the closest to the tracked object. The agent invites some nearby slave sensors to track the position of object cooperatively and inhibits other irrelevant sensors to track object. Both the overhead of communication and the sensing energy are reduced.

For saving energy, the prediction-based methods [13], [29], [30] are used to predict the location of mobile object. When a sensor detects an object, it forwards the object information to its cluster head. The information contains the location, velocity and moving direction of object. The cluster head calculates and predicts the location of object and then it multicasts wakeup information to the predicted area (forwarding area). The multicast method is called mobicast. These sensors in the forwarding area wake to perform sensing task and wait for source arrived. However, the object tracking may be failed when mobicast method meet a hollow region in sensor network. The “hole” problem is one of key issues in object tracking for WSNs.

To solve holes problem for mobicast, some protocols are proposed object tracking protocols that possess temporal delivery guarantee. Some literatures [5], [6], [15], [16], [20], [22] have been addressed for spatial and temporal delivery guarantee. Chen et al. [5], [6] builds a new shape of a forwarding zone, called the variant-egg. They utilize the variant-egg shape of the forwarding zone to achieve a high predicted accuracy by considering the factors of moving speed and direction. Huang et al. [16] presented a new face-aware mobicast routing protocol. This protocol relies on the notion of spatial neighborhoods and features a novel timed face-aware forwarding method. This protocol uses face routing to achieve high space delivery guarantee and uses timed forwarding for controlling information propagation speed.

The mobicast routing protocols for sensor networks are main designed for predicting the object moving direction. Before the object arrived, some nodes are waked up to prepare for detecting object. They do not consider how to inform mobile user the present location of target. This work proposes a novel object tracking protocol in sensor networks for mobile user. The purpose of this proposed protocol is different than that of other mobicast routing protocols. This protocol guides a mobile user to chase a mobile object and it does not need flooding request to obtain the present location of object. This protocol can track mobile object accurately and save power consumption to prolong wireless sensor network lifetime. A mobile user is called source and a tracked object is called target. The source wants to chase the target. The sensor network assist source in detecting the target and keeping the target’s track information. The sensor node keeping the track information acts as a beacon that waits for source and guides source to chase the target. The source follows the track to approach the target. To save power consumption, some sensor nodes are in active state to track target and others are into sleep state. In the course of chasing, source does not need to request the present location of target frequently. The sensor also does not need to tell the source the target location when sensor detects the target. When the source reached the location of beacon sensor, it queries the sensor to acquire the next moving position. The next position is the present location of target or the location of next beacon sensor. Source will catch the target along the sequence of beacon sensors. Due to the target moves arbitrarily, the track route does not form a straight line. For accurately tracking the target, this work utilizes face routing component to achieve spatiotemporal guarantee and solve the holes problem. Furthermore, the moving direction and velocity of target are also considered. To abridge the catch time, the sensors can cooperate to adjust the route between the target and the source dynamically. The source would reach the site of target along the adjusted route faster than along the target track. By the experimental results, this proposed protocol can save more energy than other flooding based protocols in object tracking. Therefore, this protocol can extend the lifetime of the entire wireless sensor network. Additionally, the protocol also guides a source to catch a target fast.

The rest of this paper is organized as follows. Section 2 presents the object tracking protocol for wireless sensor networks. We compare the proposed protocol with three flooding-based protocols in Section 3. The conclusions from this work are presented in Section 4.

Section snippets

Mobile object tracking

This section introduces the proposed protocol in details. The work is to focus on mobile user how to query target tracks and obtain the target position effectively. This work designs an efficient object track protocol that can decrease energy consumption and increase tracking efficacy. Assume the mobile user wants to follow a mobile object in a sensor network. First, the overview and definitions of protocol are presented. Next, the object tracking processes are introduced including target

Experimental results

This section compares the proposed dynamic object tracking (DOT) protocol with the flooding-based object tracking protocols. The experiments are implemented in ns2 simulator [27]. The version of ns2 is 2.27. The simulations use CMU’s wireless extensions [9] for the ns2 simulator. The nodes use the IEEE 802.11 radio and MAC model [17] provided by the CMU extensions. Additionally, we extend NRL’s Sensor Network [11] to ns2 simulator. This foundation consists of dual-homed sensor nodes that are


This work proposes a dynamical object tracking (DOT) protocol for sensor networks. The previous researches are almost on how to track object accurately and they do not consider the query for mobile source. Additionally, they need not report the tracking information to user. The work is to focus on mobile user how to query target tracks and obtain the target position effectively. This protocol can be applied in tiny robot (like a bee) to chase an enemy or a wild animal. The scenario is that a

Hua-Wen Tsai (

) received the B.S. degree in Information Management from Chang Jung Christian University, Taiwan, in June 1998 and the M.B.A. degree in Business and Operations Management from Chang Jung Christian University, Taiwan, in June 2001. Since September 2001, he has been working towards the Ph.D. degree and currently is a doctoral candidate in the Department of Computer Science and Information Engineering, National Cheng Kung University, Taiwan. His research interests include wireless

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    Mobile object tracking in wireless sensor networks (5)

    Hua-Wen Tsai (

    Mobile object tracking in wireless sensor networks (6)
    ) received the B.S. degree in Information Management from Chang Jung Christian University, Taiwan, in June 1998 and the M.B.A. degree in Business and Operations Management from Chang Jung Christian University, Taiwan, in June 2001. Since September 2001, he has been working towards the Ph.D. degree and currently is a doctoral candidate in the Department of Computer Science and Information Engineering, National Cheng Kung University, Taiwan. His research interests include wireless communication, ad hoc network, and sensor network.

    Mobile object tracking in wireless sensor networks (7)

    Chih-Ping Chu (

    Mobile object tracking in wireless sensor networks (8)
    ) received a B.S. degree in agricultural chemistry from National Chung Hsing University, Taiwan, an M.S. degree in computer science from the University of California, Riverside, and a Ph.D. degree in computer science from Louisiana State University. He is currently a professor in the Department of Computer Science and Information Engineering of National Cheng Kung University, Taiwan, R.O.C. His research interests include parallelizing compilers, parallel computing, parallel processing, internet computing, DNA computing, and software engineering.

    Mobile object tracking in wireless sensor networks (9)

    Tzung-Shi Chen (

    Mobile object tracking in wireless sensor networks (10)
    ) received the B.S. degree in Computer Science and Information Engineering from Tamkang University, Taiwan, in June 1989 and the Ph.D. degree in Computer Science and Information Engineering from National Central University, Taiwan, in June 1994. He joined the faculty of the Department of Information Management, Chung Jung Christian University, Tainan, Taiwan, as an Associate Professor in June 1996. Since November 2002, he has become a Professor at the Department of Information Management, Chung Jung Christian University. He was a visiting scholar at the Department of Computer Science, University of Illinois at Urbana-Champaign, USA, from June to September 2001. He was the chairman of the Department of Information Management at Chung Jung Christian University from August 2000 to July 2003. Since August 2004, he has become a Professor at the Department of Information and Learning Technology, National University of Tainan, Tainan, Taiwan. Currently, he is the chairman of the Department of Information and Learning Technology, National University of Tainan. He has served as a Guest Editor of Journal of Internet Technology, special issue on ”Wireless Ad Hoc and Sensor Networks,” 2005. He has also served as PC members on many international conferences. He co-received the best paper award of 2001 IEEE ICOIN-15. He is a member of the IEEE Computer Society. His current research interests include mobile computing and wireless networks, grid computing, mobile learning, and data mining.

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    What is tracking in WSN? ›

    Wireless sensor networks (WSNs) is a networked embedded system which comprises of spatially distributed nodes. Each node possesses sensing, processing and communication capabilities. This paper presents an object tracking method in wireless sensor network framework.

    What is the objective of wireless sensor network? ›

    Wireless Sensor Networks (WSNs) can be defined as a self-configured and infrastructure-less wireless networks to monitor physical or environmental conditions, such as temperature, sound, vibration, pressure, motion or pollutants and to cooperatively pass their data through the network to a main location or sink where ...

    Which architecture is used in wireless sensor networks? ›

    There are 2 types of architecture used in WSN: Layered Network Architecture, and Clustered Architecture.


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