954 research outputs found

    A survey of localization in wireless sensor network

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    Localization is one of the key techniques in wireless sensor network. The location estimation methods can be classified into target/source localization and node self-localization. In target localization, we mainly introduce the energy-based method. Then we investigate the node self-localization methods. Since the widespread adoption of the wireless sensor network, the localization methods are different in various applications. And there are several challenges in some special scenarios. In this paper, we present a comprehensive survey of these challenges: localization in non-line-of-sight, node selection criteria for localization in energy-constrained network, scheduling the sensor node to optimize the tradeoff between localization performance and energy consumption, cooperative node localization, and localization algorithm in heterogeneous network. Finally, we introduce the evaluation criteria for localization in wireless sensor network

    Reference Nodes Selection for Anchor-Free Localization in Wireless Sensor Networks

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    DizertačnĂ­ prĂĄce se zabĂœvĂĄ nĂĄvrhem novĂ©ho bezkotevnĂ­ho lokalizačnĂ­ho algoritmu slouĆŸĂ­cĂ­ho pro vĂœpočet pozice uzlĆŻ v bezdrĂĄtovĂœch senzorovĂœch sĂ­tĂ­ch. ProvedenĂ© studie ukĂĄzaly, ĆŸe dosavadnĂ­ bezkotevnĂ­ lokalizačnĂ­ algoritmy, pracujĂ­cĂ­ v paralelnĂ­m reĆŸimu, dosahujĂ­ malĂœch lokalizačnĂ­ch chyb. Jejich nevĂœhodou ovĆĄem je, ĆŸe pƙi sestavenĂ­ mnoĆŸiny referenčnĂ­ch uzlu spotƙebovĂĄvajĂ­ daleko větĆĄĂ­ mnoĆŸstvĂ­ energie neĆŸ algoritmy pracujĂ­cĂ­ v inkrementĂĄlnĂ­m reĆŸimu. ParalelnĂ­ lokalizačnĂ­ algoritmy vyuĆŸĂ­vajĂ­ pro určenĂ­ pozice referenčnĂ­ uzly nachĂĄzejĂ­cĂ­ se na protilehlĂœch hranĂĄch bezdrĂĄtovĂ© sĂ­tě. NovĂœ lokalizačnĂ­ algoritmus označenĂœ jako BRL (Boundary Recognition aided Localization) je zaloĆŸen na myĆĄlence decentralizovaně detekovat uzly leĆŸĂ­cĂ­ na hranici sĂ­ti a pouze z tĂ©to mnoĆŸiny vybrat potƙebnĂœ počet referenčnĂ­ch uzlu. PomocĂ­ navrĆŸenĂ©ho pƙístupu lze znaĆŸně snĂ­ĆŸit mnoĆŸstvĂ­ energie spotƙebovanĂ© v prĆŻběhu procesu vĂœběru referenčnĂ­ch uzlĆŻ v senzorovĂ©m poli. DalĆĄĂ­m pƙínosem ke snĂ­ĆŸenĂ­ energetickĂœch nĂĄroku a zĂĄroveƈ zachovĂĄnĂ­ nĂ­zkĂ© lokalizačnĂ­ chyby je vyuĆŸitĂ­ procesu multilaterace se tƙemi, eventuĂĄlně čtyƙmi referenčnĂ­mi body. V rĂĄmci prĂĄce byly provedeny simulace několika dĂ­lčích algoritmu a jejich funkčnost byla ověƙena experimentĂĄlně v reĂĄlnĂ© senzorovĂ© sĂ­ti. NavrĆŸenĂœ algoritmus BRL byl porovnĂĄn z hlediska lokalizačnĂ­ chyby a počtu zpracovanĂœch paketĆŻ s několika znĂĄmĂœmi lokalizačnĂ­mi algoritmy. VĂœsledky simulacĂ­ dokĂĄzaly, ĆŸe navrĆŸenĂœ algoritmus pƙedstavuje efektivnĂ­ ƙeĆĄenĂ­ pro pƙesnou a zĂĄroveƈ nĂ­zkoenergetickou lokalizaci uzlĆŻ v bezdrĂĄtovĂœch senzorovĂœch sĂ­tĂ­ch.The doctoral thesis is focused on a design of a novel anchor free localization algorithm for wireless sensor networks. As introduction, the incremental and concurrent anchor free localization algorithms are presented and their performance is compared. It was found that contemporary anchor free localization algorithms working in the concurrent manner achieve a low localization error, but dissipate signicant energy reserves. A new Boundary Recognition Aided Localization algorithm presented in this thesis is based on an idea to recognize the nodes placed on the boundary of network and thus reduce the number of transmission realized during the reference nodes selection phase of the algorithm. For the position estimation, the algorithm employs the multilateration technique that work eectively with the low number of the reference nodes. Proposed algorithms are tested through the simulations and validated by the real experiment with the wireless sensor network. The novel Boundary Recognition Aided Localization algorithm is compared with the known algorithms in terms of localization error and the communication cost. The results show that the novel algorithm presents powerful solution for the anchor free localization.

    Distributed Recognition of Reference Nodes for Wireless Sensor Network Localization

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    All known localization techniques for wireless sensor and ad-hoc networks require certain set of reference nodes being used for position estimation. The anchor-free techniques in contrast to anchor-based do not require reference nodes called anchors to be placed in the network area before localization operation itself, but they can establish own reference coordinate system to be used for the relative position estimation. We observed that contemporary anchor-free localization algorithms achieve a low localization error, but dissipate significant energy reserves during the recognition of reference nodes used for the position estimation. Therefore, we have proposed the optimized anchor-free localization algorithm referred to as BRL (Boundary Recognition aided Localization), which achieves a low localization error and mainly reduces the communication cost of the reference nodes recognition phase. The proposed BRL algorithm was investigated throughout the extensive simulations on the database of networks with the different number of nodes and densities and was compared in terms of communication cost and localization error with the known related algorithms such as AFL and CRP. Through the extensive simulations we have observed network conditions where novel BRL algorithm excels in comparison with the state of art

    Robust Localization from Incomplete Local Information

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    We consider the problem of localizing wireless devices in an ad-hoc network embedded in a d-dimensional Euclidean space. Obtaining a good estimation of where wireless devices are located is crucial in wireless network applications including environment monitoring, geographic routing and topology control. When the positions of the devices are unknown and only local distance information is given, we need to infer the positions from these local distance measurements. This problem is particularly challenging when we only have access to measurements that have limited accuracy and are incomplete. We consider the extreme case of this limitation on the available information, namely only the connectivity information is available, i.e., we only know whether a pair of nodes is within a fixed detection range of each other or not, and no information is known about how far apart they are. Further, to account for detection failures, we assume that even if a pair of devices is within the detection range, it fails to detect the presence of one another with some probability and this probability of failure depends on how far apart those devices are. Given this limited information, we investigate the performance of a centralized positioning algorithm MDS-MAP introduced by Shang et al., and a distributed positioning algorithm, introduced by Savarese et al., called HOP-TERRAIN. In particular, for a network consisting of n devices positioned randomly, we provide a bound on the resulting error for both algorithms. We show that the error is bounded, decreasing at a rate that is proportional to R/Rc, where Rc is the critical detection range when the resulting random network starts to be connected, and R is the detection range of each device.Comment: 40 pages, 13 figure

    Dead Reckoning Localization Technique for Mobile Wireless Sensor Networks

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    Localization in wireless sensor networks not only provides a node with its geographical location but also a basic requirement for other applications such as geographical routing. Although a rich literature is available for localization in static WSN, not enough work is done for mobile WSNs, owing to the complexity due to node mobility. Most of the existing techniques for localization in mobile WSNs uses Monte-Carlo localization, which is not only time-consuming but also memory intensive. They, consider either the unknown nodes or anchor nodes to be static. In this paper, we propose a technique called Dead Reckoning Localization for mobile WSNs. In the proposed technique all nodes (unknown nodes as well as anchor nodes) are mobile. Localization in DRLMSN is done at discrete time intervals called checkpoints. Unknown nodes are localized for the first time using three anchor nodes. For their subsequent localizations, only two anchor nodes are used. The proposed technique estimates two possible locations of a node Using Bezouts theorem. A dead reckoning approach is used to select one of the two estimated locations. We have evaluated DRLMSN through simulation using Castalia simulator, and is compared with a similar technique called RSS-MCL proposed by Wang and Zhu .Comment: Journal Paper, IET Wireless Sensor Systems, 201

    Secure Routing in Wireless Mesh Networks

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    Wireless mesh networks (WMNs) have emerged as a promising concept to meet the challenges in next-generation networks such as providing flexible, adaptive, and reconfigurable architecture while offering cost-effective solutions to the service providers. Unlike traditional Wi-Fi networks, with each access point (AP) connected to the wired network, in WMNs only a subset of the APs are required to be connected to the wired network. The APs that are connected to the wired network are called the Internet gateways (IGWs), while the APs that do not have wired connections are called the mesh routers (MRs). The MRs are connected to the IGWs using multi-hop communication. The IGWs provide access to conventional clients and interconnect ad hoc, sensor, cellular, and other networks to the Internet. However, most of the existing routing protocols for WMNs are extensions of protocols originally designed for mobile ad hoc networks (MANETs) and thus they perform sub-optimally. Moreover, most routing protocols for WMNs are designed without security issues in mind, where the nodes are all assumed to be honest. In practical deployment scenarios, this assumption does not hold. This chapter provides a comprehensive overview of security issues in WMNs and then particularly focuses on secure routing in these networks. First, it identifies security vulnerabilities in the medium access control (MAC) and the network layers. Various possibilities of compromising data confidentiality, data integrity, replay attacks and offline cryptanalysis are also discussed. Then various types of attacks in the MAC and the network layers are discussed. After enumerating the various types of attacks on the MAC and the network layer, the chapter briefly discusses on some of the preventive mechanisms for these attacks.Comment: 44 pages, 17 figures, 5 table

    1-D Coordinate Based on Local Information for MAC and Routing Issues in WSNs

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    More and more critical Wireless Sensor Networks (WSNs) applications are emerging. Those applications need reliability and respect of time constraints. The underlying mechanisms such as MAC and routing must handle such requirements. Our approach to the time constraint problem is to bound the hop-count between a node and the sink and the time it takes to do a hop so the end-to-end delay can be bounded and the communications are thus real-time. For reliability purpose we propose to select forwarder nodes depending on how they are connected in the direction of the sink. In order to be able to do so we need a coordinate (or a metric) that gives information on hop-count, that allows to strongly differentiate nodes and gives information on the connectivity of each node keeping in mind the intrinsic constraints of WSWs such as energy consumption, autonomy, etc. Due to the efficiency and scalability of greedy routing in WSNs and the financial cost of GPS chips, Virtual Coordinate Systems (VCSs) for WSNs have been proposed. A category of VCSs is based on the hop-count from the sink, this scheme leads to many nodes having the same coordinate. The main advantage of this system is that the hops number of a packet from a source to the sink is known. Nevertheless, it does not allow to differentiate the nodes with the same hop-count. In this report we propose a novel hop-count-based VCS which aims at classifying the nodes having the same hop-count depending on their connectivity and at differentiating nodes in a 2-hop neighborhood. Those properties make the coordinates, which also can be viewed as a local identifier, a very powerful metric which can be used in WSNs mechanisms.Comment: (2011
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