A protocol for tracking mobile targets using sensor networks

Yang, H.-N.; Sikdar, Biplab

doi:10.1109/snpa.2003.1203358

Cited by 269 publications

(163 citation statements)

References 9 publications

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“…It is actually a static method without considering the dynamics of target state. The latter is the distributed collaborative sensing method [26,45,46,47,51], which constructs an integrated performance index of tracking accuracy and communication cost. By optimizing the performance index online, it achieves a tradeoff between the energy cost and sensing performance.…”

Section: Related Workmentioning

confidence: 99%

Energy efficient algorithm for swarmed sensors networks

Obaidy

Ayesh

2015

Sustainable Computing: Informatics and Systems

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Section: Related Workmentioning

confidence: 99%

Energy efficient algorithm for swarmed sensors networks

Obaidy

Ayesh

2015

Sustainable Computing: Informatics and Systems

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“…The authors in [7] have proposed an object tracking strategy named multi level object tracking (MLOT) which is based on multi-level architecture for efficient object tracking and real-time recovery of missing objects by mining the movement log in sensor networks. In [8] a distributed protocol for target tracking based on static clustering has been developed that predicts the target's next location using a linear predictor. Also an efficient dynamic clustering algorithm for object tracking in [9] has been introduced that proposes a new cluster head election algorithm and helps to minimize the overlap area between clusters.…”

Section: Related Workmentioning

confidence: 99%

A New Adaptive Method for Target Tracking in Wireless Sensor Networks

Ahmadi¹,

Sabaei²,

Ahmadi³

2011

IJCA

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These days mobile target tracking is considered as one of the important applications of wireless sensor networks. In this regard, the clustering structure is one of the most applicable network structures. In this paper, we suggested a new method for target tracking that makes adaptation with target mobility model. This method utilizes two tools to create adaptability which are changing the size and shape of clusters according to target mobility model. Also by combining static and dynamic clustering a semi dynamic clustering structure has been developed to implement these tools. Simulation results show that our suggested method decreases both energy consumption by decreasing clusters size when the target moves uniformly, and tracking error by changing the size and the shape of clusters according to target mobility when the target moves unpredictably. General TermsSemi-Dynamic clustering, target tracking, tracking error.

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“…In case of hardware or circuit level, power consumption is achieved in the areas such as change over from one state to another through which tracking an object is done. Tracking multiple objects is not as simple as tracking single object due to data association problem [8]. M TT is not a trivial extension of single target tracking.…”

Section: Problem Formulationmentioning

confidence: 99%

“…The following section discusses the formulation of sub-optimal sleeping policies for solving this problem by DPTA like approaches [8].…”

Section: Figure1 Example Of Data Association Problemmentioning

confidence: 99%

A Comprehensive Review on Energy Conserved Multiobject Tracking over Wireless Sensor Networks

S.P.Ponsudha¹,

Priya²,

Edward³

2011

IJCA

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Sensor networks are used in wide variety of real-world applications including detecting, tracking and monitoring. One of the main issues in the deployment of the sensor nodes in the field of target tracking is power optimization. Various methods of target tracking are available such as making improvement in hardware, processor design etc. But still, an optimized solution to this problem is not available. To rectify this problem here we formulate the mechanism that the sensors may be put into a sleep mode with a timer that determines the sleep duration. The assumption made is that a sensor that is asleep cannot be with or waken up, and hence the sleep duration depends on the timely information it receives during the awaken period. The objective is to track the location of the objects to within the accuracy of the range of the sensor. The result is in the form of a trade-off between the energy savings and the tracking errors that result from the sleeping policies of the sensors. Sub-optimal sleeping policies that optimize this trade-off are designed, and their performance in a different tracking architecture is examined. General TermsSub optimal sleeping policies, partially observable state based formulations.

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A protocol for tracking mobile targets using sensor networks

Cited by 269 publications

References 9 publications

Energy efficient algorithm for swarmed sensors networks

Energy efficient algorithm for swarmed sensors networks

A New Adaptive Method for Target Tracking in Wireless Sensor Networks

A Comprehensive Review on Energy Conserved Multiobject Tracking over Wireless Sensor Networks

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