Secure localization and location verification in wireless sensor networks: a survey

Zeng, Yingpei; Cao, Jiannong; Hong, Ju; Zhang, Shigeng; Xie, Lihua

doi:10.1007/s11227-010-0501-4

Cited by 81 publications

(37 citation statements)

References 51 publications

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“…The algorithm implementation of wireless sensor network node optimal coverage based on improved genetic algorithm and binary ant colony algorithm is as follows [34][35][36][37][38][39]. …”

Section: Improved Genetic Algorithm and Binary Ant Colony Algorithmmentioning

confidence: 99%

Wireless sensor network node optimal coverage based on improved genetic algorithm and binary ant colony algorithm

Tian

Gao

2016

J Wireless Com Network

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Considering the situation of some practical factors such as energy saving of the nodes and the high density of distributing nodes in wireless sensor networks, a wireless sensor network (WSN) node optimal coverage method based on improved genetic algorithm and binary ant colony algorithm is proposed in this paper. The genetic algorithm and ant colony algorithm are improved and fused aiming at their disadvantages. The binary code expects a low intelligence of each ant, and each path corresponds to a comparatively small storage space, thus considerably improving the efficiency of computation. The optimal working node set is computed according to the max-coverage area of working sensor and the min-number of working sensor constraint conditions to optimize algorithm. The simulation results demonstrate that the proposed algorithm can converge at the optimal solution fast and satisfy the requirement of low node utilization rate and a high coverage rate, thus prolonging the network lifetime efficiently.

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“…The algorithm implementation of wireless sensor network node optimal coverage based on improved genetic algorithm and binary ant colony algorithm is as follows [34][35][36][37][38][39]. …”

Section: Improved Genetic Algorithm and Binary Ant Colony Algorithmmentioning

confidence: 99%

Wireless sensor network node optimal coverage based on improved genetic algorithm and binary ant colony algorithm

Tian

Gao

2016

J Wireless Com Network

View full text Add to dashboard Cite

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“…Usually, this kind of centralized algorithm has heavy communication traffic and sink nodes or background computers with strong computing power are required as well, hence it is not suitable for large scale WSN networks. There are certain related works which verify the anchor location by introducing a hidden localization verification station [11], which is also a centralized algorithm. In [12,13] rigidity theory is introduced to exclude outliers to provide reliable localization, however, rigidity theory requires pretty high ranging accuracy and it is computationally intensive.…”

Section: Reliable Localization Based On Anchor Filtrationmentioning

confidence: 99%

A Node Localization Verification Model for WSN

Chen

Dai

Chen

et al. 2016

Human Centered Computing

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Abstract. Localization is one of the most important technologies in wireless sensor networks. Range-based localization methods are widely used in many applications. However, traditional RSS-based methods cannot work well in scenarios with unreliable anchors. A reputation scheme based distributed location verification model called UNDA is proposed to solve the unreliable node recognizing issue in such scenarios. UNDA combines direct reputation and third-party reputation to recognize unreliable anchor. Furthermore, a credibilityupdating scheme is presented to make the third-party reputation more accuracy. Extensive simulation experiments indicate that the location verification algorithm has relatively high accuracy as well as low communication overhead, and the convergence of UNDA is rapid. The UNDA can be a used as an underlayer for traditional RSS-based localization algorithms to realize reliable localization.

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“…Usually, this kind of centralized algorithm has heavy communication traffic and sink nodes or background computers with strong computing power are required as well, hence it is not suitable for large scale randomly deployed WSN networks. There are certain related works which verify the anchor location by adopting a hidden localization verification station [19], which is also a centralized algorithm. In [20,21] rigidity theory is introduced to exclude outliers to provide reliable localization results, however, rigidity theory requires high ranging accuracy and it is computationally intensive.…”

Section: Related Workmentioning

confidence: 99%

Collaborative Localization and Location Verification in WSNs

Chen

Dai

Kezhen

et al. 2015

Sensors

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Localization is one of the most important technologies in wireless sensor networks. A lightweight distributed node localization scheme is proposed by considering the limited computational capacity of WSNs. The proposed scheme introduces the virtual force model to determine the location by incremental refinement. Aiming at solving the drifting problem and malicious anchor problem, a location verification algorithm based on the virtual force mode is presented. In addition, an anchor promotion algorithm using the localization reliability model is proposed to re-locate the drifted nodes. Extended simulation experiments indicate that the localization algorithm has relatively high precision and the location verification algorithm has relatively high accuracy. The communication overhead of these algorithms is relative low, and the whole set of reliable localization methods is practical as well as comprehensive.

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Secure localization and location verification in wireless sensor networks: a survey

Cited by 81 publications

References 51 publications

Wireless sensor network node optimal coverage based on improved genetic algorithm and binary ant colony algorithm

Wireless sensor network node optimal coverage based on improved genetic algorithm and binary ant colony algorithm

A Node Localization Verification Model for WSN

Collaborative Localization and Location Verification in WSNs

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