10,641 research outputs found
Design and realization of precise indoor localization mechanism for Wi-Fi devices
Despite the abundant literature in the field, there is still the need to find a time-efficient, highly accurate, easy to deploy and robust localization algorithm for real use. The algorithm only involves minimal human intervention. We propose an enhanced Received Signal Strength Indicator (RSSI) based positioning algorithm for Wi-Fi capable devices, called the Dynamic Weighted Evolution for Location Tracking (DWELT). Due to the multiple phenomena affecting the propagation of radio signals, RSSI measurements show fluctuations that hinder the utilization of straightforward positioning mechanisms from widely known propagation loss models. Instead, DWELT uses data processing of raw RSSI values and applies a weighted posterior-probabilistic evolution for quick convergence of localization and tracking. In this paper, we present the first implementation of DWELT, intended for 1D location (applicable to tunnels or corridors), and the first step towards a more generic implementation. Simulations and experiments show an accuracy of 1m in more than 81% of the cases, and less than 2m in the 95%.Peer ReviewedPostprint (published version
Gossip Algorithms for Distributed Signal Processing
Gossip algorithms are attractive for in-network processing in sensor networks
because they do not require any specialized routing, there is no bottleneck or
single point of failure, and they are robust to unreliable wireless network
conditions. Recently, there has been a surge of activity in the computer
science, control, signal processing, and information theory communities,
developing faster and more robust gossip algorithms and deriving theoretical
performance guarantees. This article presents an overview of recent work in the
area. We describe convergence rate results, which are related to the number of
transmitted messages and thus the amount of energy consumed in the network for
gossiping. We discuss issues related to gossiping over wireless links,
including the effects of quantization and noise, and we illustrate the use of
gossip algorithms for canonical signal processing tasks including distributed
estimation, source localization, and compression.Comment: Submitted to Proceedings of the IEEE, 29 page
Two-Hop Routing with Traffic-Differentiation for QoS Guarantee in Wireless Sensor Networks
This paper proposes a Traffic-Differentiated Two-Hop Routing protocol for
Quality of Service (QoS) in Wireless Sensor Networks (WSNs). It targets WSN
applications having different types of data traffic with several priorities.
The protocol achieves to increase Packet Reception Ratio (PRR) and reduce
end-to-end delay while considering multi-queue priority policy, two-hop
neighborhood information, link reliability and power efficiency. The protocol
is modular and utilizes effective methods for estimating the link metrics.
Numerical results show that the proposed protocol is a feasible solution to
addresses QoS service differenti- ation for traffic with different priorities.Comment: 13 page
Deterministic Secure Positioning in Wireless Sensor Networks
Properly locating sensor nodes is an important building block for a large
subset of wireless sensor networks (WSN) applications. As a result, the
performance of the WSN degrades significantly when misbehaving nodes report
false location and distance information in order to fake their actual location.
In this paper we propose a general distributed deterministic protocol for
accurate identification of faking sensors in a WSN. Our scheme does \emph{not}
rely on a subset of \emph{trusted} nodes that are not allowed to misbehave and
are known to every node in the network. Thus, any subset of nodes is allowed to
try faking its position. As in previous approaches, our protocol is based on
distance evaluation techniques developed for WSN. On the positive side, we show
that when the received signal strength (RSS) technique is used, our protocol
handles at most faking sensors. Also, when the
time of flight (ToF) technique is used, our protocol manages at most misbehaving sensors. On the negative side, we prove
that no deterministic protocol can identify faking sensors if their number is
. Thus our scheme is almost optimal with respect
to the number of faking sensors. We discuss application of our technique in the
trusted sensor model. More precisely our results can be used to minimize the
number of trusted sensors that are needed to defeat faking ones
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