598 research outputs found
RTXP : A Localized Real-Time Mac-Routing Protocol for Wireless Sensor Networks
Protocols developed during the last years for Wireless Sensor Networks (WSNs)
are mainly focused on energy efficiency and autonomous mechanisms (e.g.
self-organization, self-configuration, etc). Nevertheless, with new WSN
applications, appear new QoS requirements such as time constraints. Real-time
applications require the packets to be delivered before a known time bound
which depends on the application requirements. We particularly focus on
applications which consist in alarms sent to the sink node. We propose
Real-Time X-layer Protocol (RTXP), a real-time communication protocol. To the
best of our knowledge, RTXP is the first MAC and routing real-time
communication protocol that is not centralized, but instead relies only on
local information. The solution is cross-layer (X-layer) because it allows to
control the delays due to MAC and Routing layers interactions. RTXP uses a
suited hop-count-based Virtual Coordinate System which allows deterministic
medium access and forwarder selection. In this paper we describe the protocol
mechanisms. We give theoretical bound on the end-to-end delay and the capacity
of the protocol. Intensive simulation results confirm the theoretical
predictions and allow to compare with a real-time centralized solution. RTXP is
also simulated under harsh radio channel, in this case the radio link
introduces probabilistic behavior. Nevertheless, we show that RTXP it performs
better than a non-deterministic solution. It thus advocates for the usefulness
of designing real-time (deterministic) protocols even for highly unreliable
networks such as WSNs
Estimating distances via connectivity in wireless sensor networks
Distance estimation is vital for localization and many other applications in wireless sensor networks. In this paper, we develop a method that employs a maximum-likelihood estimator to estimate distances between a pair of neighboring nodes in a static wireless sensor network using their local connectivity information, namely the numbers of their common and non-common one-hop neighbors. We present the distance estimation method under a generic channel model, including the unit disk (communication) model and the more realistic log-normal (shadowing) model as special cases. Under the log-normal model, we investigate the impact of the log-normal model uncertainty; we numerically evaluate the bias and standard deviation associated with our method, which show that for long distances our method outperforms the method based on received signal strength; and we provide a Cramér-Rao lower bound analysis for the problem of estimating distances via connectivity and derive helpful guidelines for implementing our method. Finally, on implementing the proposed method on the basis of measurement data from a realistic environment and applying it in connectivity-based sensor localization, the advantages of the proposed method are confirmed. Copyright © 2012 John Wiley & Sons, Ltd
Sidelobe Control in Collaborative Beamforming via Node Selection
Collaborative beamforming (CB) is a power efficient method for data
communications in wireless sensor networks (WSNs) which aims at increasing the
transmission range in the network by radiating the power from a cluster of
sensor nodes in the directions of the intended base station(s) or access
point(s) (BSs/APs). The CB average beampattern expresses a deterministic
behavior and can be used for characterizing/controling the transmission at
intended direction(s), since the mainlobe of the CB beampattern is independent
on the particular random node locations. However, the CB for a cluster formed
by a limited number of collaborative nodes results in a sample beampattern with
sidelobes that severely depend on the particular node locations. High level
sidelobes can cause unacceptable interference when they occur at directions of
unintended BSs/APs. Therefore, sidelobe control in CB has a potential to
increase the network capacity and wireless channel availability by decreasing
the interference. Traditional sidelobe control techniques are proposed for
centralized antenna arrays and, therefore, are not suitable for WSNs. In this
paper, we show that distributed, scalable, and low-complexity sidelobe control
techniques suitable for CB in WSNs can be developed based on node selection
technique which make use of the randomness of the node locations. A node
selection algorithm with low-rate feedback is developed to search over
different node combinations. The performance of the proposed algorithm is
analyzed in terms of the average number of trials required to select the
collaborative nodes and the resulting interference. Our simulation results
approve the theoretical analysis and show that the interference is
significantly reduced when node selection is used with CB.Comment: 30 pages, 10 figures, submitted to the IEEE Trans. Signal Processin
Localisation in wireless sensor networks for disaster recovery and rescuing in built environments
A thesis submitted to the University of Bedfordshire in partial fulfilment of the requirements for the degree of Doctor of PhilosophyProgress in micro-electromechanical systems (MEMS) and radio frequency (RF) technology has fostered the development of wireless sensor networks (WSNs). Different from traditional networks, WSNs are data-centric, self-configuring and self-healing. Although WSNs have been successfully applied in built environments (e.g. security and services in smart homes), their applications and benefits have not been fully explored in areas such as disaster recovery and rescuing. There are issues related to self-localisation as well as practical constraints to be taken into account.
The current state-of-the art communication technologies used in disaster scenarios are challenged by various limitations (e.g. the uncertainty of RSS). Localisation in WSNs (location sensing) is a challenging problem, especially in disaster environments and there is a need for technological developments in order to cater to disaster conditions. This research seeks to design and develop novel localisation algorithms using WSNs to overcome the limitations in existing techniques. A novel probabilistic fuzzy logic based range-free localisation algorithm (PFRL) is devised to solve localisation problems for WSNs. Simulation results show that the proposed algorithm performs better than other range free localisation algorithms (namely DVhop localisation, Centroid localisation and Amorphous localisation) in terms of localisation accuracy by 15-30% with various numbers of anchors and degrees of radio propagation irregularity.
In disaster scenarios, for example, if WSNs are applied to sense fire hazards in building, wireless sensor nodes will be equipped on different floors. To this end, PFRL has been extended to solve sensor localisation problems in 3D space. Computational results show that the 3D localisation algorithm provides better localisation accuracy when varying the system parameters with different communication/deployment models. PFRL is further developed by applying dynamic distance measurement updates among the moving sensors in a disaster environment. Simulation results indicate that the new method scales very well
On the Impact of Geometry on Ad Hoc Communication in Wireless Networks
In this work we address the question how important is the knowledge of
geometric location and network density to the efficiency of (distributed)
wireless communication in ad hoc networks. We study fundamental communication
task of broadcast and develop well-scalable, randomized algorithms that do not
rely on GPS information, and which efficiency formulas do not depend on how
dense the geometric network is. We consider two settings: with and without
spontaneous wake-up of nodes. In the former setting, in which all nodes start
the protocol at the same time, our algorithm accomplishes broadcast in rounds under the SINR model, with high probability (whp), where
is the diameter of the communication graph and is the number of
stations. In the latter setting, in which only the source node containing the
original message is active in the beginning, we develop a slightly slower
algorithm working in rounds whp. Both algorithms are based on a
novel distributed coloring method, which is of independent interest and
potential applicability to other communication tasks under the SINR wireless
model
Self-organising an indoor location system using a paintable amorphous computer
This thesis investigates new methods for self-organising a precisely defined pattern of intertwined number sequences which may be used in the rapid deployment of a passive indoor positioning system's infrastructure.A future hypothetical scenario is used where computing particles are suspended in paint and covered over a ceiling. A spatial pattern is then formed over the covered ceiling. Any small portion of the spatial pattern may be decoded, by a simple camera equipped device, to provide a unique location to support location-aware pervasive computing applications.Such a pattern is established from the interactions of many thousands of locally connected computing particles that are disseminated randomly and densely over a surface, such as a ceiling. Each particle has initially no knowledge of its location
or network topology and shares no synchronous clock or memory with any other particle.The challenge addressed within this thesis is how such a network of computing particles that begin in such an initial state of disarray and ignorance can, without outside intervention or expensive equipment, collaborate to create a relative coordinate system. It shows how the coordinate system can be created to be coherent, even in the face of obstacles, and closely represent the actual shape of the networked surface itself. The precision errors incurred during the propagation of the coordinate system are identified and the distributed algorithms used to avoid this error are explained and demonstrated through simulation.A new perimeter detection algorithm is proposed that discovers network edges and other obstacles without the use of any existing location knowledge. A new distributed localisation algorithm is demonstrated to propagate a relative coordinate system throughout the network and remain free of the error introduced by the network perimeter that is normally seen in non-convex networks. This localisation algorithm operates without prior configuration or calibration, allowing the coordinate system to be deployed without expert manual intervention or on networks that are otherwise inaccessible.The painted ceiling's spatial pattern, when based on the proposed localisation algorithm, is discussed in the context of an indoor positioning system
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