15,206 research outputs found
GPS-free Positioning in Mobile Ad-Hoc Networks
In this paper we consider the problem of node positioning in ad-hoc networks. We propose a distributed, infrastructure-free positioning algorithm that does not rely on Global Positioning System (GPS). The algorithm uses the distances between the nodes to build a relative coordinate system in which the node positions are computed in two dimensions. The main contribution of this work is to define and compute relative positions of the nodes in an ad-hoc network without using GPS. We further explain how the proposed approach can be applied to wide area ad-hoc networks
Techniques for Communication and Geolocation using Wireless Ad hoc Networks
Networks with hundreds of ad hoc nodes equipped with communication and position finding abilities are conceivable with recent advancements in technology. Methods are presented in this thesis to assess the communicative capabilities and node position estimation of mobile ad hoc networks. Specifically, we investigate techniques for providing communication and geolocation with specific characteristics in wireless ad hoc networks. The material presented in this thesis, communication and geolocation, may initially seem a collection of disconnected topics related only distantly under the banner of ad hoc networks. However, systems currently in development combining these techniques into single integrated systems. In this thesis first, we investigate the effect of multilayer interaction, including fading and path loss, on ad hoc routing protocol performance, and present a procedure for deploying an ad hoc network based on extensive simulations. Our first goal is to test the routing protocols with parameters that can be used to characterize the environment in which they might be deployed. Second, we analyze the location discovery problem in ad hoc networks and propose a fully distributed, infrastructure-free positioning algorithm that does not rely on the Global Positioning System (GPS). The algorithm uses the approximate distances between the nodes to build a relative coordinate system in which the node positions are computed in three-dimensions. However, in reconstructing three-dimensional positions from approximate distances, we need to consider error threshold, graph connectivity, and graph rigidity. We also statistically evaluate the location discovery procedure with respect to a number of parameters, such as error propagation and the relative positions of the nodes
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 re¬stricted isometry property. Later, the 1-sparse vector can be exactly recovered by compressive sensing. Finally, as the 1-sparse vector is approximate sparse, weighted Cen¬troid 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
Requirement analysis for building practical accident warning systems based on vehicular ad-hoc networks
An Accident Warning System (AWS) is a safety application that provides collision avoidance notifications for next generation vehicles whilst Vehicular Ad-hoc Networks (VANETs) provide the communication functionality to exchange these notifi- cations. Despite much previous research, there is little agreement on the requirements for accident warning systems. In order to build a practical warning system, it is important to ascertain the system requirements, information to be exchanged, and protocols needed for communication between vehicles. This paper presents a practical model of an accident warning system by stipulating the requirements in a realistic manner and thoroughly reviewing previous proposals with a view to identify gaps in this area
Distributed and adaptive location identification system for mobile devices
Indoor location identification and navigation need to be as simple, seamless,
and ubiquitous as its outdoor GPS-based counterpart is. It would be of great
convenience to the mobile user to be able to continue navigating seamlessly as
he or she moves from a GPS-clear outdoor environment into an indoor environment
or a GPS-obstructed outdoor environment such as a tunnel or forest. Existing
infrastructure-based indoor localization systems lack such capability, on top
of potentially facing several critical technical challenges such as increased
cost of installation, centralization, lack of reliability, poor localization
accuracy, poor adaptation to the dynamics of the surrounding environment,
latency, system-level and computational complexities, repetitive
labor-intensive parameter tuning, and user privacy. To this end, this paper
presents a novel mechanism with the potential to overcome most (if not all) of
the abovementioned challenges. The proposed mechanism is simple, distributed,
adaptive, collaborative, and cost-effective. Based on the proposed algorithm, a
mobile blind device can potentially utilize, as GPS-like reference nodes,
either in-range location-aware compatible mobile devices or preinstalled
low-cost infrastructure-less location-aware beacon nodes. The proposed approach
is model-based and calibration-free that uses the received signal strength to
periodically and collaboratively measure and update the radio frequency
characteristics of the operating environment to estimate the distances to the
reference nodes. Trilateration is then used by the blind device to identify its
own location, similar to that used in the GPS-based system. Simulation and
empirical testing ascertained that the proposed approach can potentially be the
core of future indoor and GPS-obstructed environments
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 localization’s 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 beacons’ 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
Jumps: Enhancing hop-count positioning in sensor networks using multiple coordinates
Positioning systems in self-organizing networks generally rely on
measurements such as delay and received signal strength, which may be difficult
to obtain and often require dedicated equipment. An alternative to such
approaches is to use simple connectivity information, that is, the presence or
absence of a link between any pair of nodes, and to extend it to hop-counts, in
order to obtain an approximate coordinate system. Such an approximation is
sufficient for a large number of applications, such as routing. In this paper,
we propose Jumps, a positioning system for those self-organizing networks in
which other types of (exact) positioning systems cannot be used or are deemed
to be too costly. Jumps builds a multiple coordinate system based solely on
nodes neighborhood knowledge. Jumps is interesting in the context of wireless
sensor networks, as it neither requires additional embedded equipment nor
relies on any nodes capabilities. While other approaches use only three
hop-count measurements to infer the position of a node, Jumps uses an arbitrary
number. We observe that an increase in the number of measurements leads to an
improvement in the localization process, without requiring a high dense
environment. We show through simulations that Jumps, when compared with
existing approaches, reduces the number of nodes sharing the same coordinates,
which paves the way for functions such as position-based routing
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