Exploiting Opportunistic Interactions for Localization in Heterogeneous Wireless Systems (original) (raw)

Context-aware peer-to-peer and cooperative positioning

International Conference on Localization and GNSS 2014 (ICL-GNSS 2014), 2014

Peer-to-peer and cooperative positioning represent one of the major evolutions for mass-market positioning, bringing together capabilities of Satellite Navigation and Communication Systems. It is well known that smartphones already provide user position leveraging both GNSS and information collected through the communication network (e.g., Assisted-GNSS). However, exploiting the exchange of information among close users can attain further benefits. In this paper, we deal with such an approach and show that sharing information on the environmental conditions that characterize the reception of satellite signals can be effectively exploited to improve the accuracy and availability of user positioning. This approach extends the positioning service to indoor environments and, in general, to any scenario where full visibility of the satellite constellation cannot be granted. I.

Heterogeneous Cooperative Localization for Social Networks

International Journal of Wireless Information Networks, 2013

Location-aware techniques has become a hot research topic with great value in commercial and military applications. Cooperative localization, which utilizes multiple sensors in portable devices to estimate locations of the mobile users in the social networks, is one of the most promising solution for the indoor geo-location. Traditional cooperative localization methods are ranging based, they are highly dependent on the distance interpreted from the Received Signal Strength (RSS) or Time of Arrival (TOA) from anchors. However, a precise ranging procedure demands high performance hardware which would increase the cost to the current mobile platform. In this paper, we describes four ranging-free probabilistic cooperative localization algorithms: Centroid method, Nearest Neighbor method, Kernel method and AP density method to improve the accuracy for the indoor geo-location using current mobile devices. Since the GPS sensor embedded in the smart phone is able to provide accurate location information in the outdoor area, those mobile nodes can be used as calibrated anchors. The position of the indoor mobile node can be estimated by exchanging locations and RSSs from shared wireless access points (APs) information between the target node and anchor nodes. An empirical evaluation of the system is given to demonstrate the feasibility of these cooperative localization algorithms by reporting the results in a real-world environments, e.g. suburban area and Boston downtown. Moreover, we compared our results with the WiFi positioning system (WPS) made by Skyhook Wireless to validate the accuracy of the proposed algorithms. Meanwhile, a Monte Carlo simulation is also carried out to evaluate the performance of the cooperative algorithms under different scenarios. Results show that given the same scenario setting, the AP density method and Kernel method outperform than other methods.

Position Certainty Propagation: A Localization Service for Ad-Hoc Networks

Computers, 2019

Location services for ad-hoc networks are of indispensable value for a wide range of applications, such as the Internet of Things (IoT) and vehicular ad-hoc networks (VANETs). Each context requires a solution that addresses the specific needs of the application. For instance, IoT sensor nodes have resource constraints (i.e., computational capabilities), and so a localization service should be highly efficient to conserve the lifespan of these nodes. We propose an optimized energy-aware and low computational solution, requiring 3-GPS equipped nodes (anchor nodes) in the network. Moreover, the computations are lightweight and can be implemented distributively among nodes. Knowing the maximum range of communication for all nodes and distances between 1-hop neighbors, each node localizes itself and shares its location with the network in an efficient manner. We simulate our proposed algorithm in a NS-3 simulator, and compare our solution with state-of-the-art methods. Our method is capa...

Localized positioning in ad hoc networks

Ad Hoc Networks, 2003

Position centric approaches, such as Cartesian routing, geographic routing, and the recently proposed trajectory based forwarding (TBF), address scalability issues in large ad hoc networks by using Euclidean space as a complementary name space. These approaches require that nodes know their position in a common coordinate system. While a GPS receiver in each node would be ideal, in many cases an approximation algorithm is necessary for networks with only a few GPS enabled nodes. These algorithms however require collaboration of large portions of the network, thus imposing an overhead for nodes which do not need positioning, or are mobile. We propose Local Positioning System (LPS), a method that makes use of local node capabilities -angle of arrival, range estimations, compasses and accelerometers, in order to internally position only the groups of nodes involved in particular conversations. Localized positioning enables position centric uses, like discovery, flooding and routing in networks where global positioning is not available.

Position Certainty Propagation: A Location Service for MANETs

Lecture Notes in Computer Science, 2019

Localization in Mobile Ad-hoc Networks (MANETs) and Wireless Sensor Networks (WSNs) is an issue of great interest, especially in applications such as the IoT and VANETs. We propose a solution that overcomes two limiting characteristics of these types of networks. The first is the high cost of nodes with a location sensor (such as GPS) which we will refer to as anchor nodes. The second is the low computational capability of nodes in the network. The proposed algorithm addresses two issues; self-localization where each non-anchor node should discover its own position, and global localization where a node establishes knowledge of the position of all the nodes in the network. We address the problem as a graph where vertices are nodes in the network and edges indicate connectivity between nodes. The weights of edges represent the Euclidean distance between the nodes. Given a graph with at least three anchor nodes and knowing the maximum communication range for each node, we are able to localize nodes using fairly simple computations in a moderately dense graph.

Improved Position Estimation in Wireless Heterogeneous Networks

Lecture Notes in Computer Science, 2004

This paper addresses the problern of nodes localization in wireless ad hoc networks. Two types of nodes are considered: nodes with self-locating capability like GPS and nodes with no self-locating capability. For the last ones it is thus important to infer a position which will be retrieved from the position of the neighbor's nodes. The precision of this information clearly depends on the environment and may not be very accurate. We propose a method which consists in selecting and processing only nodes that are likely to enhance the accuracy of an estimated position. We focus our approach on defining a hull, made up of neighboring nodes, as a key element of position accuracy enhancement. The improvements of using such a method are then validated by a set of simulations.

A simulation model for localization of pervasive objects using heterogeneous wireless networks

Simulation Modelling Practice and Theory, 2011

The Internet of Things is an emergent paradigm, which enables new solutions and applications in many contexts of every-day life. Object and persons become themselves part of Internet of Things when they can be discovered, identified and profiled in the real world by information services. Position represents a relevant attribute needed by many applications, whose contexts are characterized by pervasiveness of the objects/things in the considered scenarios. In order to infer positions of pervasive objects, which are not either equipped with any location-sensing technologies, or are unable to locate themselves, it is needed to support them with an appropriate infrastructure, which allows to determine their position in a manner that is transparent to the applications. Deficiencies of the current positioning systems affect some usual or critical scenarios. In order to overcome these limitations, cooperation of mobile smart devices, which are able to interact with the environment surrounding, can be exploited as a layer of an open-standard based architecture for inferring location information through heterogeneous wireless networks.