Conference Paper

Time-Bounded Essential Localization for Wireless Sensor Networks

DOI: 10.1109/TNET.2012.2200107 Conference: Fifth International Conference on Networking, Architecture, and Storage, NAS 2010, Macau, China, July 15-17, 2010
Source: DBLP


In many practical applications of wireless sensor networks, it is crucial to accomplish the localization of sensors within a given time bound. We find that the traditional definition of relative localization is inappropriate for evaluating its actual overhead in localization time. To address this issue, we define a novel problem called essential localization and present the first rigorous study on the essential localizability of a wireless sensor network within a given time bound. Additionally, we propose an efficient distributed algorithm for time-bounded essential localization over a sensor network and evaluate the performance of the algorithm with analysis and extensive simulation studies.

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    • "• Time Localization: is the number of communication rounds required to merge all the LCS of each island in a single LCS. • Time Essential Localization: is the number of communication rounds expected to translate each LCS to any LCS island [7]. • The relative localizability of network at a given time bound: a wireless sensor network is relatively localizable in k rounds of communications if and only if all sensor nodes are localized in their local coordinate systems and all local coordinate systems converge to only one LCSI in k communication rounds. "
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    ABSTRACT: Many applications of Wireless Sensor Networks (WSN) require to achieve the positions of the sensor nodes within a given time bound. In this paper we study the relative and physical localizability of WSN in a given time bound. We propose a new distributed and time bounded localization algorithm based on Multidimensional Scaling (MDS) method in WSN called D-MDS localization time algorithm. We compare the proposed algorithm to the existing algorithm based on the well-known Trilateration method. The simulation results show that the proposed algorithm outperforms the existing approach based on Trilateration method in terms of the number of localized nodes in the network and the number of anchors required to physically localize the sensors. The D-MDS localization time algorithm localizes a large number of nodes for a low node degree in a time bound. Moreover it is able to physically localize the network with a low number of anchors compared with the algorithm based on Trilateration method.
    Full-text · Conference Paper · Jun 2014
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    • "where (x j , y j ) denotes the Cartesian coordinates of node j. We can work out E i j-result With H result and some other parameters as follows:(19)where α is the data compression ratio. When E i j-storage , E i j-query , and E i j-result are all worked out, E i j in Formula (6) can be worked out. "
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    ABSTRACT: In-network data storage and retrieval is one of the most important problems in wireless sensor networks. Many schemes have been proposed to solve this problem. However, most of them do not take the frequencies of event and query into consideration. In fact, the frequencies of event and query are very important factors in real applications of in-network data storage and retrieval. In this paper, we introduce a virtual-ring-based data storage and retrieval scheme, which is called VRS, to solve the problem. VRS divides the whole sensor network field into some virtual rings. According to the frequencies, one of the virtual rings is selected out as the rendezvous ring, which plays the role of a bridge between the information consumers and the information producers. Extensive experiments have been done to evaluate the performance of the proposed scheme, VRS. Simulation results show that VRS outperforms the existing work in load balance, delay of data storage and retrieval, and the lifetime of the sensor networks.
    Full-text · Article · Nov 2012 · International Journal of Distributed Sensor Networks
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    ABSTRACT: This paper addresses the problem of target counting based on the Monte Carlo simulation. We rely on an Accept-Reject process to guide the placement of virtual targets in a virtual sensor field, which has exactly the same sensor layout as the real one. The objective of this construction is to generate a virtual target energy landscape whose shape is close enough to an energy landscape estimated from the real sensor readings. Based on the number of virtual targets placed on the virtual field and the total virtual and real target energy volumes, the number of real targets can be estimated. We consider both single-epoch and multi-epoch sensor readings and our theoretical analysis indicates that by exploiting the information from multiple epochs, our approach yields a target count that approximately converges to the true target count when the number of epochs is large enough. Extensive comparison based simulation study has been performed and the results verify the effectiveness of our target counting algorithms.
    Preview · Conference Paper · Jul 2011
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