A Fine-Grained Localization Scheme Using a Mobile Beacon Node for Wireless Sensor Networks

Liu, Kezhong; Xiong, Ji; Cui, Yongqiang; Han, Dong

doi:10.1109/csa.2009.5404332

Cited by 7 publications

(3 citation statements)

References 16 publications

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“…The DSN has a sink node, to which all sensor devices send their sensed data packets in multi-hop fashion. Each sensor S i has a fixed and known location (x i , y i ), determined by GPS or any other localization method [23]. Each sensor device is uniquely identified by its ID, which we assume an integer number.…”

Section: Network Model and Assumptionsmentioning

confidence: 99%

Network lifetime aware area coverage for clustered directional sensor networks

Sharmin

Nur

Razzaque

et al. 2015

2015 International Conference on Networking Systems and Security (NSysS)

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The problem of field or area coverage in Directional Sensor Networks (DSNs) presents huge research challenges including appropriate selection of sensors with their active sensing directions in an energy-efficient way. Existing solutions permit to execute coverage enhancement algorithms in each individual sensor nodes, leading to high communication and computation overheads, loss of energy and reduced accuracy. In this paper, we have proposed a novel network lifetime aware area coverage solution, NLAC, for a clustered DSN, where distributed cluster heads (CHs) have the responsibility of determining the number of active member nodes and their sensing directions. The CHs minimizes the overlapping coverage area and energy consumption by switching more nodes in sleep state. The proposed NLAC system is fully distributed and it exploits single-hop neighborhood information only. Results from extensive simulations, show that NLAC system offers better performance in terms of covering area and networklife.

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Section: Network Model and Assumptionsmentioning

confidence: 99%

Network lifetime aware area coverage for clustered directional sensor networks

Sharmin

Nur

Razzaque

et al. 2015

2015 International Conference on Networking Systems and Security (NSysS)

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“…The distances between an unknown node and its neighbour sensor nodes constrain the location of the unknown node. Bayesian inference [5], trigonometric algorithm [6], multi‐dimensional scaling [7], multilateration [8, 9] or generalised geometrical localisation algorithms [10] can be utilised to estimate node location. The range‐free algorithms use borderline or area measurement techniques.…”

Section: Related Workmentioning

confidence: 99%

“…Some existing mobile beacon‐assisted localisation algorithms adopt a random movement path, such as the random waypoint (RWP) model [9] and the random direction mobility model [8]; however, these random paths cannot cover the entire ROI. The path‐planning problem has been investigated since its proposal [5].…”

Section: Related Workmentioning

confidence: 99%

Obstacle‐avoidance path planning of a mobile Beacon for localisation

Wang¹,

Cui

Guo

et al. 2013

IET wirel. sens. syst.

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Location is important for most wireless sensor network applications. A potential localisation method uses a mobile beacon instead of numerous static beacons. This method includes planning a beacon trajectory as a fundamental and interesting problem. Obstacles in practical scenarios often restrict the free locomotion of beacons. This study examines the obstacle-avoidance path-planning method, which consists of three stages. First, the network deployment region is partitioned into cells by adaptive cell decomposition, and the corresponding connectivity graph is constructed. Second, a modified max-min ant system algorithm is provided to obtain the approximate shortest global path that covers the connectivity graph. Finally, a sequence of concentric circles of adjustable radii is utilised as the local path within an obstacle-free cell. We prove that all sensor nodes deployed in obstacle-free cells can be localised by using the proposed path. Simulation results show that more than 90% of the sensor nodes in the obstacle-free region can be localised by using the given trajectory.

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ELPMA: Efficient Localization Algorithm Based Path Planning for Mobile Anchor in Wireless Sensor Network

Gumaida

Luo

2018

Wireless Pers Commun

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A Fine-Grained Localization Scheme Using a Mobile Beacon Node for Wireless Sensor Networks

Cited by 7 publications

References 16 publications

Network lifetime aware area coverage for clustered directional sensor networks

Network lifetime aware area coverage for clustered directional sensor networks

Obstacle‐avoidance path planning of a mobile Beacon for localisation

ELPMA: Efficient Localization Algorithm Based Path Planning for Mobile Anchor in Wireless Sensor Network

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