1,130 research outputs found
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
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
Dead Reckoning Localization Technique for Mobile Wireless Sensor Networks
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
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.
Locating sensors with fuzzy logic algorithms
In a system formed by hundreds of sensors deployed
in a huge area it is important to know the position where every
sensor is.
This information can be obtained using several methods.
However, if the number of sensors is high and the deployment
is based on ad-hoc manner, some auto-locating techniques must
be implemented.
In this paper we describe a novel algorithm based on fuzzy
logic with the objective of estimating the location of sensors
according to the knowledge of the position of some reference
nodes.
This algorithm, called LIS (Localization based on Intelligent
Sensors) is executed distributively along a wireless sensor network
formed by hundreds of nodes, covering a huge area.
The evaluation of LIS is led by simulation tests. The result
obtained shows that LIS is a promising method that can easily
solve the problem of knowing where the sensors are located.Junta de AndalucĂa P07-TIC-0247
LIS: Localization based on an intelligent distributed fuzzy system applied to a WSN
The localization of the sensor nodes is a fundamental problem in wireless sensor networks.
There are a lot of different kinds of solutions in the literature. Some of them use external
devices like GPS, while others use special hardware or implicit parameters in wireless
communications.
In applications like wildlife localization in a natural environment, where the power available
and the weight are big restrictions, the use of hungry energy devices like GPS or hardware
that add extra weight like mobile directional antenna is not a good solution.
Due to these reasons it would be better to use the localizationâs implicit characteristics in
communications, such as connectivity, number of hops or RSSI. The measurement related
to these parameters are currently integrated in most radio devices. These measurement
techniques are based on the beaconsâ transmissions between the devices.
In the current study, a novel tracking distributed method, called LIS, for localization of
the sensor nodes using moving devices in a network of static nodes, which have no additional
hardware requirements is proposed.
The position is obtained with the combination of two algorithms; one based on a local
node using a fuzzy system to obtain a partial solution and the other based on a centralized
method which merges all the partial solutions. The centralized algorithm is based on the
calculation of the centroid of the partial solutions.
Advantages of using fuzzy system versus the classical Centroid Localization (CL)
algorithm without fuzzy preprocessing are compared with an ad hoc simulator made for
testing localization algorithms.
With this simulator, it is demonstrated that the proposed method obtains less localization
errors and better accuracy than the centroid algorithm.Junta de AndalucĂa P07-TIC-0247
Overlapping Multi-hop Clustering for Wireless Sensor Networks
Clustering is a standard approach for achieving efficient and scalable
performance in wireless sensor networks. Traditionally, clustering algorithms
aim at generating a number of disjoint clusters that satisfy some criteria. In
this paper, we formulate a novel clustering problem that aims at generating
overlapping multi-hop clusters. Overlapping clusters are useful in many sensor
network applications, including inter-cluster routing, node localization, and
time synchronization protocols. We also propose a randomized, distributed
multi-hop clustering algorithm (KOCA) for solving the overlapping clustering
problem. KOCA aims at generating connected overlapping clusters that cover the
entire sensor network with a specific average overlapping degree. Through
analysis and simulation experiments we show how to select the different values
of the parameters to achieve the clustering process objectives. Moreover, the
results show that KOCA produces approximately equal-sized clusters, which
allows distributing the load evenly over different clusters. In addition, KOCA
is scalable; the clustering formation terminates in a constant time regardless
of the network size
Sparse Localization with a Mobile Beacon Based on LU Decomposition in Wireless Sensor Networks
Node localization is the core in wireless sensor network. It can be solved by powerful beacons, which are equipped with global positioning system devices to know their location information. In this article, we present a novel sparse localization approach with a mobile beacon based on LU decomposition. Our scheme firstly translates node localization problem into a 1-sparse vector recovery problem by establishing sparse localization model. Then, LU decomposition pre-processing is adopted to solve the problem that measurement matrix does not meet the reÂŹstricted isometry property. Later, the 1-sparse vector can be exactly recovered by compressive sensing. Finally, as the 1-sparse vector is approximate sparse, weighted CenÂŹtroid scheme is introduced to accurately locate the node. Simulation and analysis show that our scheme has better localization performance and lower requirement for the mobile beacon than MAP+GC, MAP-M, and MAP-M&N schemes. In addition, the obstacles and DOI have little effect on the novel scheme, and it has great localization performance under low SNR, thus, the scheme proposed is robust
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