Node Location Discovery in Ad hoc and Sensor Networks (original) (raw)
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Node Positioning in Ad Hoc Wireless Sensor Networks
2006 IEEE International Conference on Industrial Informatics, 2006
Locating the sensor nodes in an ad hoc wireless sensor network (WSN) is a very challenging task. In general, the network nodes are not synchronised and the internal delays within the sensor nodes may be unknown. As a result, the positioning problem can not be solved by simply using the triangulation method and certain prior information must be provided. In this paper, we consider a scenario where there are a number of nodes whose positions are known, and it is required to locate the other mobile or static sensor nodes within the radio range of each other by measuring the time of arrival (TOA) in the whole system. Two algorithms are employed, the direct method and the linear least squares (LS) estimator. The performance of the two algorithms is investigated. In particular an analytical formula is derived to estimate the performance of the LS estimator. Simulation results agree well with theoretical predictions.
Radio Communications, 2010
An ad hoc 1 network is defined as a decentralised wireless network that is set up on-the-fly for a specific purpose. These networks were proposed years ago for military use, with the purpose of communicating devices in a highly constrained scenario. Under such a network, devices join and leave the network dynamically; thus, it cannot be expected to have any kind of network infrastructure. This wish for decentralised on-the-fly networks has subsequently expanded to cover several fields besides the military. Today, there are several mobile services requiring the self-organising capabilities that ad hoc networks offer. Examples include packet tracking, online-gaming, and measuring systems, among others. Ad hoc networks have obvious benefits for mobile services, but they also introduce new issues that regular network protocols cannot cope with, including optimum routing, network fragmentation, reduced calculation power, energy-constrained terminals, etc. In ad hoc networks, positioning takes a significant role, mainly due to the on-the-fly condition. In fact, several services require nodes to know the position of the customers in order to perform their duty properly. Wireless sensor networks concentrate most of the services that need positioning to perform their duty. Such networks constitute a subset of ad hoc networks involving dense topologies operating in an ad hoc fashion, and they are composed of small, energy and computation constrained terminals. In ad hoc networks, and especially in wireless sensor networks, nodes are spread over a certain area without a precise knowledge about the topology. In fact, this topology is variable. Accordingly, there are several unknowns (e.g., node density and coverage, network's energy map, the presence of shadowed zones, nodes' placement in the network coverage area) that are likely to constrain the performance of ad hoc services. Knowledge of the terminals' locations can substantially improve the service performance. Positioning is not only important for the service provisioning; it is also crucial in the ad hoc protocol stack development. Due to the changes in the topology and the lack of communication infrastructure, ad hoc protocols have to address several issues not present in regular cellular networks. Routing is one of the best examples of the dependence of ad hoc networks on positioning. Studies such as (Stojmenovic, 2002) demonstrate that only position-based routing protocols are scalable, i.e., able to cope with a higher density of 1 "Ad hoc" is actually a Latin phrase that means "to this (thing, purpose, end, etc.)" 31 www.intechopen.com Radio Communications 620 nodes in the network. The same seems to apply to other management and operation tasks in ad hoc networks. 1.1 The Location problem in ad hoc networks Nodes in an ad hoc network can be grouped into three categories according to the positioning capabilities: beacon nodes, settled nodes, and unknown nodes. Beacon nodes, also known as anchors or landmarks, are those able to compute their position on their own, i.e., without using an ad hoc location algorithm. Accordingly, they implement at least one location technique (e.g., GPS, map matching), which can be used as standalone. Beacon nodes usually constitute the reference frame necessary to set up a location algorithm. Unknown nodes are those nodes that do not know their position yet. When an ad hoc network is set up, all nodes except the beacon nodes are unknown. Settled nodes are unknown nodes that are able to compute their position from the information that they exchange with beacon nodes and/or other settled nodes. The purpose of the ad hoc location system is thus to position as many nodes as possible, turning them from unknown to settled nodes (Bourkerche et al., 2007). Location systems in ad hoc networks function in two steps: local positioning and positioning algorithm. The former is responsible for computing the position of an unknown node from the metrics gathered. The second step consists of the positioning algorithm, which indicates how the position information is managed in order to maximise the number of nodes being settled. 1.2 Measuring the performance of location solutions Performance of location solutions in ad hoc networks can be computed according to several parameters. The main ones are presented below. 1.2.1 Accuracy Ad hoc positioning requires good accuracy since most of the networks in ad hoc mode are deployed in constrained scenarios, often indoors. In such environments, accuracy is especially relevant, since a few meters of error in the position may cause the node to be identified in another room, floor, or even building. Furthermore, nodes are expected to be very close (e.g., in medical applications), and inaccurate positions could hinder operation and maintenance tasks or even prevent location-based applications from performing their duty. Thus, location algorithms for ad hoc networks must produce positions for settled nodes of the highest possible accuracy.
Wireless Sensor Networks: nodes localization issue
2004
This paper examines the problem of determining node location in ad-hoc sensor networks. Spatial localization is an important building block for wireless sensor networks. Beacons that know their position and serve as reference are a vital aspect of nearly every localization system. The intention of this paper is to examine the work done to locate nodes and the use of beacon nodes in order to decrease the error of nodes localization.
Node Localization in Wireless Sensor Networks
When we talk about the improvement in the wireless communication technologies, we come across the topic of wireless sensor networks (WSN). Sensor nodes have evolved from just giving out information, to processing information and communicating with the different nodes of a network. The bulky structure of the node is reduced to a miniature one, also their resistance to various environmental conditions. Basically, the sensor nodes are designed to sense the physical phenomenon, process the data and transmit to the base station. Earlier the location of the sensor was known and hence there was an ease of operation. For various applications, the locations of nodes are not predetermined and are deployed randomly. Thus, their exact locations must be known. Localization information represents the geographic coordinates of the physical location of the node. In other words, we determine the position of nodes for communication and detection.
Analysis of Node Localization in Wireless Sensor Networks
2012
1. Abstract Sensor networks are dense wireless networks of small, low-cost sensors, which collect and disseminate environmental data. Sensor nodes are very small, lightweight, and unobtrusive. The problem of localization, that is, “determining where a given node is physically located in a network”, can be mainly divided into two parts range-based (fine-grained) or range-free (coarse-grained) schemes. This Paper presents the analysis of range based algorithms on the basis of few network parameters (Network Size, Anchor node Density, Array node density) and tried to find out the best range based algorithms by doing simulation on matlab. The metric selected for the analysis is Standard Deviation of localization error.
DV Based Positioning in Ad Hoc Networks
Telecommunication Systems, 2003
Many ad hoc network protocols and applications assume the knowledge of geographic location of nodes. The absolute position of each networked node is an assumed fact by most sensor networks which can then present the sensed information on a geographical map. Finding position without the aid of GPS in each node of an ad hoc network is important in cases where GPS is either not accessible, or not practical to use due to power, form factor or line of sight conditions. Position would also enable routing in sufficiently isotropic large networks, without the use of large routing tables. We are proposing APS -a distributed, hop by hop positioning algorithm, that works as an extension of both distance vector routing and GPS positioning in order to provide approximate position for all nodes in a network where only a limited fraction of nodes have self positioning capability.
Localization of Sensor Node in Wireless Sensor Network
2015
Wireless sensor networks (WSNs) have become very popular nowadays because they are widely used in military application, tracking the object, forest fire detection, disaster management, in navigation systems and many more applications. Implementing the WSNs has large number of benefits as well as obstacles. There are several issues in WSN such as security, data aggregation, data dissemination, data routing, localization etc. Localization is the challenging issue, because without knowing the location of the data where it is coming from, processing that data becomes totally inappropriate. Finding the location of the unknown sensor node using anchor node is localization of that node. Anchor nodes or the beacon nodes are the nodes with Global Positioning System (GPS) in it. Taking these anchor nodes as reference nodes we are finding out the position of the unknown sensor nodes. In this work we are proposing range based localization algorithm using modified quadrilateral approach. Here we...
Dynamic fine-grained localization in ad-hoc networks of sensors
Proceedings of the 7th …, 2001
Wireless communication systems have become increasingly common because of advances in radio and embedded system technologies. In recent years, a new class of applications that networks these wireless devices together is evolving. A representative of this class that has received considerable attention from the research community is the wireless sensor network. Such a sensor networks consist of numerous tetherless devices that are released into the environment and organize themselves in an adhoc fashion. The goal of the network is to perform a monitoring task, and knowledge the physical location of the individual nodes is therefore essential. Not only is this information needed for the sensor network to report the location where events take place, it also assists in group-querying or routing traffic to a designated geographic destination and provides information on physical network coverage. However, equipping every node with a GPS receiver is not always feasible due to possible obstructions in the path of the satellite signals or energy limitations in the nodes. In this paper, we present a novel location discovery approach, which we call AHLoS (Ad-Hoc Localization System), for wireless sensor networks. Only a small fraction of the nodes start with knowledge of their location and the others dynamically estimate their positions via a distributed algorithm. Furthermore, our algorithm utilizes a new iterative multi-lateration technique, such that all nodes that meet some simple connectivity requirements are eventually able to determine their position. We have analyzed the operation of AHLoS, designed a new testbed of wireless sensor nodes and verified the behavior of our distributed localization technique. The results obtained from the testbed are then incorporated in a simulation platform to perform scalability tests and evaluate the effects of error propagation.