Anchor nodes placement for effective passive localization

Akl, Robert; Pasupathy, Karthik; Haidar, Mohamad

doi:10.1109/icost.2011.6085823

Cited by 25 publications

(26 citation statements)

References 7 publications

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“…ey compared the positioning performance obtained from different RN placements, such as comparing the placement of various basic geometric layouts [9], symmetrical/unsymmetrical layouts [10], or overlapping and hierarchical clustering [11]. Other system design researches aimed at developing the RN-placement techniques to determine the optimum number and location.…”

Section: Introductionmentioning

confidence: 99%

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Robust System Design Using BILP for Wireless Indoor Positioning Systems

Maneerat

Kaemarungsi

2018

Mobile Information Systems

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In wireless indoor positioning system designs, reference node (RN) failures during the online phase cause received signal strength values to be unavailable. is leads to accuracy performance degradation and a lack of system reliability in smart office systems. Moreover, the major design concern in the reliability of indoor positioning systems under the faulty RNs during the online phase has not been yet investigated in previous works. To address these gaps, we propose a novel mathematical formulation using a Binary Integer Linear Programming (BILP) approach that employs the Simulated Annealing (SA) solution technique. e proposed robust system design aims to put in place a suitable number of RNs and to determine their optimum locations, which may be located on a single floor or on multiple floors. In particular, the proposed system design provisions to support robust operation both during a normal situation and when there are some RN failures. Experimental results and comparative performance evaluation revealed that the proposed robust system design outperformed other system designs and was able to achieve the highest location accuracy performance in both fault-free and RN-failure scenarios. Specifically, when nine of the RNs in a three-story building failed, the proposed system design achieved 84.6%, 54.7%, and 32.9% more accurate performance than the Uniform, the MSMR, and the PhI-Uni, respectively.

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Section: Introductionmentioning

confidence: 99%

“…In [9][10][11], the authors investigated the impact of reference node (RN) placement on location accuracy performance.…”

Section: Introductionmentioning

confidence: 99%

Robust System Design Using BILP for Wireless Indoor Positioning Systems

Maneerat

Kaemarungsi

2018

Mobile Information Systems

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“…Localization schemes are referred to as Anchor-Based or Anchor free if the technique involves estimating the location of the unknown sensor node in reference to an anchor node or without reference to an anchor node respectively [4] [5]. Anchor nodes as shown in figure 1, are those nodes in the network that know their location by means of direct deployment at known coordinates, hard coding the location into the hardware or acquired by using locational systems such as a Global Positioning System (GPS) receiver [1] [6][7][8][9]. The anchor nodes in figure 1 acts as both cluster heads and reference nodes with which all other nodes determine their location.…”

Section: Introductionmentioning

confidence: 99%

Radio Coverage Analysis of Anchor Nodes for the Localization and Monitoring of Smart Energy Meters (SEM)

Klogo¹,

Gadze²,

Diawuo³

2014

IJCA

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This paper evaluates the radio coverage of anchor nodes and reliability in an anchor-based wireless sensor network platform used in locating and monitoring smart energy meters. Knowledge of the location of smart energy meters is critical for network functionalities such as monitoring, billing and energy budget planning. One efficient technique of determining the location of field monitoring and measuring devices such as smart energy meters is the anchor-based localization. Anchor-based localization is a technique in which the unknown node's location is determined with reference to a location aware node. Anchor-based localization techniques require anchor nodes having good radio coverage to the unknown nodes. The error associated with localization is high when anchor nodes are not optimally accessed by unknown nodes in the network. This paper performed a radio coverage analysis and evaluated the reliability of anchor nodes within a network perimeter for the localization and monitoring of smart energy meters. An outage probability was used to verify reliability of the network for the localization and monitoring of the smart energy meters. Our result show that for a 100by100 meter perimeter, four anchor nodes will provide good reliability of radio coverage for the localization and monitoring of smart energy meters.

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“…For example, Shang et al [2] randomly place anchors in their experiment and find that a selection of collinear anchors in one test is rather unlucky. Recently, Akl et al [3] study the anchor placement for passive positioning, and they find that the optimal placement is that no three anchor nodes are collinear at the center of network. The authors of [4] point out that the optimal placement of anchors should be around the corners of the network and also find that the more nonlinearity results in the better positioning performance.…”

Section: Related Workmentioning

confidence: 99%

“…We named this method the artificial calibration. Also, many works [2,3] have pointed out that optimizing the anchor placement is able to accelerate the convergence of the positioning algorithm and improve the positioning accuracy. Nevertheless, this kind of methods always suffers from the complicated and errorprone mapping between physical locations and the node IDs, which is even more severe in a large sensor network.…”

Section: Introductionmentioning

confidence: 99%

Efficient Deterministic Anchor Deployment for Sensor Network Positioning

Chen

Zhu

et al. 2013

International Journal of Distributed Sensor Networks

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Sensor network positioning systems have been extensively studied in recent years. Most of the systems share a common assumption that some known-position anchor nodes have existed. However, a more fundamental question is always being overlooked, that is, how to acquire the anchor's position. In general, GPS-based measures and the artificial calibration are two dominant methods to acquire anchor positions. Due to the high energy cost and failures in occlusion regions of the GPS modules, the artificial calibration method is adopted extensively. Nevertheless, numerous disadvantages of the artificial calibration, such as the expensive labor cost and error-prone features, also make it hard to be an efficient solution for the anchor positioning. For this reason, we design an efficient mapping algorithm between anchors and their positions (MD-SKM) to avoid the complicated artificial calibration. Additionally, we propose a best feature matching (BFM) method to further relax the restriction of MDS-KM where three or more calibrated anchors are needed. We evaluate our MDS-KM algorithm under various topologies and connectivity settings. Experiment results show that at a slightly higher connectivity level, our algorithm can achieve the exactly correct matching between anchors and their positions without any calibrated anchors.

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Anchor nodes placement for effective passive localization

Cited by 25 publications

References 7 publications

Robust System Design Using BILP for Wireless Indoor Positioning Systems

Robust System Design Using BILP for Wireless Indoor Positioning Systems

Radio Coverage Analysis of Anchor Nodes for the Localization and Monitoring of Smart Energy Meters (SEM)

Efficient Deterministic Anchor Deployment for Sensor Network Positioning

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