7,334 research outputs found
Achieving Small World Properties using Bio-Inspired Techniques in Wireless Networks
It is highly desirable and challenging for a wireless ad hoc network to have
self-organization properties in order to achieve network wide characteristics.
Studies have shown that Small World properties, primarily low average path
length and high clustering coefficient, are desired properties for networks in
general. However, due to the spatial nature of the wireless networks, achieving
small world properties remains highly challenging. Studies also show that,
wireless ad hoc networks with small world properties show a degree distribution
that lies between geometric and power law. In this paper, we show that in a
wireless ad hoc network with non-uniform node density with only local
information, we can significantly reduce the average path length and retain the
clustering coefficient. To achieve our goal, our algorithm first identifies
logical regions using Lateral Inhibition technique, then identifies the nodes
that beamform and finally the beam properties using Flocking. We use Lateral
Inhibition and Flocking because they enable us to use local state information
as opposed to other techniques. We support our work with simulation results and
analysis, which show that a reduction of up to 40% can be achieved for a
high-density network. We also show the effect of hopcount used to create
regions on average path length, clustering coefficient and connectivity.Comment: Accepted for publication: Special Issue on Security and Performance
of Networks and Clouds (The Computer Journal
Network Topology Mapping from Partial Virtual Coordinates and Graph Geodesics
For many important network types (e.g., sensor networks in complex harsh
environments and social networks) physical coordinate systems (e.g.,
Cartesian), and physical distances (e.g., Euclidean), are either difficult to
discern or inapplicable. Accordingly, coordinate systems and characterizations
based on hop-distance measurements, such as Topology Preserving Maps (TPMs) and
Virtual-Coordinate (VC) systems are attractive alternatives to Cartesian
coordinates for many network algorithms. Herein, we present an approach to
recover geometric and topological properties of a network with a small set of
distance measurements. In particular, our approach is a combination of shortest
path (often called geodesic) recovery concepts and low-rank matrix completion,
generalized to the case of hop-distances in graphs. Results for sensor networks
embedded in 2-D and 3-D spaces, as well as a social networks, indicates that
the method can accurately capture the network connectivity with a small set of
measurements. TPM generation can now also be based on various context
appropriate measurements or VC systems, as long as they characterize different
nodes by distances to small sets of random nodes (instead of a set of global
anchors). The proposed method is a significant generalization that allows the
topology to be extracted from a random set of graph shortest paths, making it
applicable in contexts such as social networks where VC generation may not be
possible.Comment: 17 pages, 9 figures. arXiv admin note: substantial text overlap with
arXiv:1712.1006
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
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
Energy efficient routing towards a mobile sink using virtual coordinates in a wireless sensor network
The existence of a coordinate system can often improve the routing in a wireless sensor network. While most coordinate systems correspond to the geometrical or geographical coordinates, in recent years researchers had proposed the use of virtual coordinates. Virtual coordinates depend only on the topology of the network as defined by the connectivity of the nodes, without requiring geographical information. The work in this thesis extends the use of virtual coordinates to scenarios where the wireless sensor network has a mobile sink. One reason to use a mobile sink is to distribute the energy consumption more evenly among the sensor nodes and thus extend the life-time of the network. We developed two algorithms, MS-DVCR and CU-DVCR which perform routing towards a mobile sink using virtual coordinates. In contrast to the baseline virtual coordinate routing MS-DVCR limits routing updates triggered by the sink movement to a local area around the sink. In contrast, CU-DVCR limits the route updates to a circular area on the boundary of the local area. We describe the design justification and the implementation of these algorithms. Using a set of experimental studies, we show that MS-DVCR and CU-DVCR achieve a lower energy consumption compared to the baseline virtual coordinate routing without any noticeable impact on routing performance. In addition, CU-DVCR provides a lower energy consumption than MS-DVCR for the case of a fast moving sink
Double-Directional Information Azimuth Spectrum and Relay Network Tomography for a Decentralized Wireless Relay Network
A novel channel representation for a two-hop decentralized wireless relay
network (DWRN) is proposed, where the relays operate in a completely
distributive fashion. The modeling paradigm applies an analogous approach to
the description method for a double-directional multipath propagation channel,
and takes into account the finite system spatial resolution and the extended
relay listening/transmitting time. Specifically, the double-directional
information azimuth spectrum (IAS) is formulated to provide a compact
representation of information flows in a DWRN. The proposed channel
representation is then analyzed from a geometrically-based statistical modeling
perspective. Finally, we look into the problem of relay network tomography
(RNT), which solves an inverse problem to infer the internal structure of a
DWRN by using the instantaneous doubledirectional IAS recorded at multiple
measuring nodes exterior to the relay region
Virtual and topological coordinate based routing, mobility tracking and prediction in 2D and 3D wireless sensor networks
2013 Fall.Includes bibliographical references.A Virtual Coordinate System (VCS) for Wireless Sensor Networks (WSNs) characterizes each sensor node's location using the minimum number of hops to a specific set of sensor nodes called anchors. VCS does not require geographic localization hardware such as Global Positioning System (GPS), or localization algorithms based on Received Signal Strength Indication (RSSI) measurements. Topological Coordinates (TCs) are derived from Virtual Coordinates (VCs) of networks using Singular Value Decomposition (SVD). Topology Preserving Maps (TPMs) based on TCs contain 2D or 3D network topology and directional information that are lost in VCs. This thesis extends the scope of VC and TC based techniques to 3D sensor networks and networks with mobile nodes. Specifically, we apply existing Extreme Node Search (ENS) for anchor placement for 3D WSNs. 3D Geo-Logical Routing (3D-GLR), a routing algorithm for 3D sensor networks that alternates between VC and TC domains is evaluated. VC and TC based methods have hitherto been used only in static networks. We develop methods to use VCs in mobile networks, including the generation of coordinates, for mobile sensors without having to regenerate VCs every time the topology changes. 2D and 3D Topological Coordinate based Tracking and Prediction (2D-TCTP and 3D-TCTP) are novel algorithms developed for mobility tracking and prediction in sensor networks without the need of physical distance measurements. Most existing 2D sensor networking algorithms fail or perform poorly in 3D networks. Developing VC and TC based algorithms for 3D sensor networks is crucial to benefit from the scalability, adjustability and flexibility of VCs as well as to overcome the many disadvantages associated with geographic coordinate systems. Existing ENS algorithm for 2D sensor networks plays a key role in providing a good anchor placement and we continue to use ENS algorithm for anchor selection in 3D network. Additionally, we propose a comparison algorithm for ENS algorithm named Double-ENS algorithm which uses two independent pairs of initial anchors and thereby increases the coverage of ENS anchors in 3D networks, in order to further prove if anchor selection from original ENS algorithm is already optimal. Existing Geo-Logical Routing (GLR) algorithm demonstrates very good routing performance by switching between greedy forwarding in virtual and topological domains in 2D sensor networks. Proposed 3D-GLR extends the algorithm to 3D networks by replacing 2D TCs with 3D TCs in TC distance calculation. Simulation results show that the 3D-GLR algorithm with ENS anchor placement can significantly outperform current Geographic Coordinates (GCs) based 3D Greedy Distributed Spanning Tree Routing (3D-GDSTR) algorithm in various network environments. This demonstrates the effectiveness of ENS algorithm and 3D-GLR algorithm in 3D sensor networks. Tracking and communicating with mobile sensors has so far required the use of localization or geographic information. This thesis presents a novel approach to achieve tracking and communication without geographic information, thus significantly reducing the hardware cost and energy consumption. Mobility of sensors in WSNs is considered under two scenarios: dynamic deployment and continuous movement. An efficient VC generation scheme, which uses the average of neighboring sensors' VCs, is proposed for newly deployed sensors to get coordinates without flooding based VC generation. For the second scenario, a prediction and tracking algorithm called 2D-TCTP for continuously moving sensors is developed for 2D sensor networks. Predicted location of a mobile sensor at a future time is calculated based on current sampled velocity and direction in topological domain. The set of sensors inside an ellipse-shaped detection area around the predicted future location is alerted for the arrival of mobile sensor for communication or detection purposes. Using TPMs as a 2D guide map, tracking and prediction performances can be achieved similar to those based on GCs. A simple modification for TPMs generation is proposed, which considers radial information contained in the first principle component from SVD. This modification improves the compression or folding at the edges that has been observed in TPMs, and thus the accuracy of tracking. 3D-TCTP uses a detection area in the shape of a 3D sphere. 3D-TCTP simulation results are similar to 2D-TCTP and show competence comparable to the same algorithms based on GCs although without any 3D geographic information
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