Low-connectivity and full-coverage three dimensional wireless sensor networks

Bai, Xin; Zhang, Chuanlin; Xuan, Dong; Teng, Jin; Jia, Weijia

doi:10.1145/1530748.1530768

Cited by 56 publications

(33 citation statements)

References 25 publications

(39 reference statements)

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“…This is the optimal sensor deployment problem. We plan to follow the research of [4,33] and design optimal AP and camera deployment patterns as a part of our future work. On the other hand, in real implementation, we may need a database and a mechanism, such as [29], for recording, managing and searching through electronic and visual signals and the final location results.…”

Section: Discussionmentioning

confidence: 99%

EV-Loc: Integrating Electronic and Visual Signals for Accurate Localization

Teng

Zhang

Zhu³

et al. 2014

IEEE/ACM Trans. Networking

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Nowadays, an increasing number of objects can be represented by their wireless electronic identifiers. For example, people can be recognized by their phone numbers or their phones' WiFi MAC addresses and products can be identified by their RFID numbers. Localizing objects with electronic identifiers is increasingly important as our lives become increasingly "digitalized". However, traditional wireless localization techniques cannot meet the fast growing needs of accurate and cost efficient localization. Some of these techniques require expensive hardware to achieve high accuracy, which is impractical for massive deployment. Others, such as WiFi RSSI based localization, are inaccurate and not robust to environmental noise. In this paper, we propose a new localization technique called EV-Loc. In EV-Loc, we use visual signals to help improve the accuracy of wireless localization. Our technique fully leverages visual signals' high accuracy and electronic signals' pervasiveness. To effectively couple these two signals, we design an E-V match engine to find the correspondence between an object's electronic identifier and its visual appearance. We implement our technique on mobile devices and evaluate it in real-world scenarios. The localization error is less than 1 m. We also evaluate our approach using large scale simulations. The results show that our approach is accurate and robust.

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Section: Discussionmentioning

confidence: 99%

EV-Loc: Integrating Electronic and Visual Signals for Accurate Localization

Teng

Zhang

Zhu³

et al. 2014

IEEE/ACM Trans. Networking

Self Cite

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“…For determined deployment, the sensors can be deployed along the road-side, or at a metro station, etc. The Sand [12] sensor network for target tracking and the CitySense [1] network for urban monitoring are the instances where optimal patterns can be provided [13]. However, lots of routing protocols are designed for random deployment.…”

Section: Topologymentioning

confidence: 99%

Utility-Based Routing in Wireless Sensor Networks

2013

The Art of Wireless Sensor Networks

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Wireless sensor networks (WSNs) have been proposed for monitoring physical environments. The applications in WSNs have comprised a wide variety of scenarios. The design of routing protocols in WSNs becomes more complicated than the traditional network when we consider the energy cost, throughput, reliability, and delay as routing metrics. Selecting a particular routing protocol mainly depends on the capabilities of the nodes, and on the requirements of the application. In this chapter, we will briefly discuss the existing utility-based routing protocols for WSNs. We put them into several categories according to their utility properties, such as delay, cost, and packet delivery ratio. In addition, we will also cover the composition-based utility for wireless networks and its extensions in low duty-cycle WSNs.

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“…Alam and Haas [20] proposed a deployment pattern that generates the Voronoi tessellation of truncated octahedron in 3D space. Achieving full-coverage and k-connectivity in three-dimensional space, some lattice was proposed in [21] and [22].Wu et al [23] used Delaunay Triangulation to solve the coverage problem and finding the position of sensors in the environment. Vieira et al [24] use computational geometry and graph theory to find a solution.…”

Section: Related Workmentioning

confidence: 99%