Fault-Tolerant Target Localization in Sensor Networks

Deng, Min; Liu, Fang; Thaeler, Andrew; Chen, Dechang; Cheng, Xiuzhen

doi:10.1155/2007/96742

Cited by 52 publications

(36 citation statements)

References 23 publications

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“…EV-Loc is largely centralized, like most current existing localization algorithms [10,3,2,5,13]. In some circumstances, a distributed algorithm is desirable for efficiency and privacy reasons.…”

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

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“…• The intensity σ of each record in the 23 × 23 grid was randomly chosen from [0,3]. The respective value in the 32 × 32 grid was [0,6].…”

Section: A Simulation Modelmentioning

confidence: 99%

“…There is an increasing number of applications and fields where sensors can be used [6]. Some examples would be to monitor the environment [11] (severe weather, fires, earthquakes, volcanoes), to help in constructions (energy preserving buildings, building integrity) and agriculture (effective watering), to use for military purposes [3], [8] (sense mines, target detection and tracking) and many more. All these applications have different characteristics, which mean that often different protocols need to adapt the network architecture to satisfy each one.…”

Section: Introductionmentioning

confidence: 99%

Query Sensitive Storage for Wireless Sensor Networks

Papadimitriou

Katsaros

Manolopoulos

2009

2009 13th Panhellenic Conference on Informatics

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Abstract-Storage management in wireless sensor networks is an area that has started to attract significant attention, and several methods have been proposed, such as Local Storage (LS), Data-Centric Storage (DCS) and more recently LocationCentric Storage (LCS). Several modern applications, like contextdependent information dissemination for pervasive computing, on-demand warning in surveillance sensor networks and roadway safety warning, require that each originating event is stored around its point of origin. LCS is a suitable approach for such applications. Though, LCS does not take into consideration the origin of the queries, which is equally important to the storage method, because it has immediate influence on the experienced latency. This paper proposes a simple yet effective way of reducing the network latency, namely the Query Sensitive Storage (QSS) protocol. QSS makes certain that not only will the queries be answered, but all subsequent queries that originated in the same area will be answered faster. The experimental evaluation using the J-Sim simulator attests that with the proposed QSS protocol we can achieve smaller network latency at a minimum storage cost as compared to its state-of-the-art competitor, namely LCS.

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“…These sensors can be used to detect land mines, enemy tanks [4], etc. LCS can be employed for on-demand warning.…”

Section: B On-demand Warning In Surveillance Sensor Networkmentioning

confidence: 99%

“…There exist many exciting sensor network applications, including smart learning [27], battlefields [8], [9], environmental monitoring and control [3], [13], [17], [19], target detection and tracking [4], [18], [20], roadway safety warning [25], [26], etc. These applications are expected to have strong economic influence in the near future.…”

Section: Introductionmentioning

confidence: 99%

On the Performance of Location-Centric Storage in Sensor Networks

Xing

Cheng

2007

International Conference on Wireless Algorithms, Systems and Applications (WASA 2007)

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Abstract-This paper presents Location-Centric Storage (LCS), a novel distributed data storage protocol for sensor networks. In the protocol, each event detected by sensors is associated with an intensity value (σ)(by sensors), where σ is a parameter that depends on the characteristics of the event and the application context. When event information is broadcast, a sensor decides whether to store the record of an event by checking its distance to the event location and the σ. In general, the higher the intensity of an event, the further its information can propagate geographically in the sensor network. Besides, the closer to the event location, the denser the sensors are that store the event information, and thus the quicker and better a user can know about the event (by reading from surrounding sensors). The protocol utilizes network resource efficiently. In particular, the storage load of sensors is independent of the network size, and is evenly distributed across the network. Moreover, the communication distance for getting event information is small. Therefore, the protocol has great scalability. We provide detailed theoretical analysis and simulation study to support the claims. We also ran simulations to show the advantage of our protocol over some previous work. LCS can be used for applications such as context-dependent information mining in pervasive computing and on-demand warning in surveillance sensor networks.

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Fault-Tolerant Target Localization in Sensor Networks

Cited by 52 publications

References 23 publications

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

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

Query Sensitive Storage for Wireless Sensor Networks

On the Performance of Location-Centric Storage in Sensor Networks

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