4,063 research outputs found
A survey of localization in wireless sensor network
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
DizertaÄnĂ prĂĄce se zabĂ˝vĂĄ nĂĄvrhem novĂŠho bezkotevnĂho lokalizaÄnĂho algoritmu slouĹžĂcĂho pro vĂ˝poÄet pozice uzlĹŻ v bezdrĂĄtovĂ˝ch senzorovĂ˝ch sĂtĂch. ProvedenĂŠ studie ukĂĄzaly, Ĺže dosavadnĂ bezkotevnĂ lokalizaÄnĂ algoritmy, pracujĂcĂ v paralelnĂm reĹžimu, dosahujĂ malĂ˝ch lokalizaÄnĂch chyb. Jejich nevĂ˝hodou ovĹĄem je, Ĺže pĹi sestavenĂ mnoĹžiny referenÄnĂch uzlu spotĹebovĂĄvajĂ daleko vÄtĹĄĂ mnoĹžstvĂ energie neĹž algoritmy pracujĂcĂ v inkrementĂĄlnĂm reĹžimu. ParalelnĂ lokalizaÄnĂ algoritmy vyuĹžĂvajĂ pro urÄenĂ pozice referenÄnĂ uzly nachĂĄzejĂcĂ se na protilehlĂ˝ch hranĂĄch bezdrĂĄtovĂŠ sĂtÄ. NovĂ˝ lokalizaÄnĂ algoritmus oznaÄenĂ˝ jako BRL (Boundary Recognition aided Localization) je zaloĹžen na myĹĄlence decentralizovanÄ detekovat uzly leĹžĂcĂ na hranici sĂti a pouze z tĂŠto mnoĹžiny vybrat potĹebnĂ˝ poÄet referenÄnĂch uzlu. PomocĂ navrĹženĂŠho pĹĂstupu lze znaĹžnÄ snĂĹžit mnoĹžstvĂ energie spotĹebovanĂŠ v prĹŻbÄhu procesu vĂ˝bÄru referenÄnĂch uzlĹŻ v senzorovĂŠm poli. DalĹĄĂm pĹĂnosem ke snĂĹženĂ energetickĂ˝ch nĂĄroku a zĂĄroveĹ zachovĂĄnĂ nĂzkĂŠ lokalizaÄnĂ chyby je vyuĹžitĂ procesu multilaterace se tĹemi, eventuĂĄlnÄ ÄtyĹmi referenÄnĂmi body. V rĂĄmci prĂĄce byly provedeny simulace nÄkolika dĂlÄĂch algoritmu a jejich funkÄnost byla ovÄĹena experimentĂĄlnÄ v reĂĄlnĂŠ senzorovĂŠ sĂti. NavrĹženĂ˝ algoritmus BRL byl porovnĂĄn z hlediska lokalizaÄnĂ chyby a poÄtu zpracovanĂ˝ch paketĹŻ s nÄkolika znĂĄmĂ˝mi lokalizaÄnĂmi algoritmy. VĂ˝sledky simulacĂ dokĂĄzaly, Ĺže navrĹženĂ˝ algoritmus pĹedstavuje efektivnĂ ĹeĹĄenĂ pro pĹesnou a zĂĄroveĹ nĂzkoenergetickou lokalizaci uzlĹŻ v bezdrĂĄtovĂ˝ch senzorovĂ˝ch 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.
Robust Localization from Incomplete Local Information
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
Reliable multi-hop routing with cooperative transmissions in energy-constrained networks
We present a novel approach in characterizing the optimal reliable multi-hop virtual multiple-input single-output (vMISO) routing in ad hoc networks. Under a high node density regime, we determine the optimal cardinality of the cooperation
sets at each hop on a path minimizing the total energy cost per transmitted bit. Optimal cooperating set cardinality curves are derived, and they can be used to determine the optimal routing strategy based on the required reliability, transmission power, and path loss coefficient. We design a new greedy geographical
routing algorithm suitable for vMISO transmissions, and demonstrate the applicability of our results for more general networks
Distributed Recognition of Reference Nodes for Wireless Sensor Network Localization
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
Efficient AoA-based wireless indoor localization for hospital outpatients using mobile devices
The motivation of this work is to help outpatients find their corresponding departments or clinics, thus, it needs to provide indoor positioning services with a room-level accuracy. Unlike wireless outdoor localization that is dominated by the global positioning system (GPS), wireless indoor localization is still an open issue. Many different schemes are being developed to meet the increasing demand for indoor localization services. In this paper, we investigated the AoA-based wireless indoor localization for outpatientsâ wayfinding in a hospital, where Wi-Fi access points (APs) are deployed, in line, on the ceiling. The target position can be determined by a mobile device, like a smartphone, through an efficient geometric calculation with two known APs coordinates and the angles of the incident radios. All possible positions in which the target may appear have been comprehensively investigated, and the corresponding solutions were proven to be the same. Experimental results show that localization error was less than 2.5 m, about 80% of the time, which can satisfy the outpatientsâ requirements for wayfinding
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