6,708 research outputs found
Visualizing Sensor Network Coverage with Location Uncertainty
We present an interactive visualization system for exploring the coverage in
sensor networks with uncertain sensor locations. We consider a simple case of
uncertainty where the location of each sensor is confined to a discrete number
of points sampled uniformly at random from a region with a fixed radius.
Employing techniques from topological data analysis, we model and visualize
network coverage by quantifying the uncertainty defined on its simplicial
complex representations. We demonstrate the capabilities and effectiveness of
our tool via the exploration of randomly distributed sensor networks
On the Distribution of Random Geometric Graphs
Random geometric graphs (RGGs) are commonly used to model networked systems
that depend on the underlying spatial embedding. We concern ourselves with the
probability distribution of an RGG, which is crucial for studying its random
topology, properties (e.g., connectedness), or Shannon entropy as a measure of
the graph's topological uncertainty (or information content). Moreover, the
distribution is also relevant for determining average network performance or
designing protocols. However, a major impediment in deducing the graph
distribution is that it requires the joint probability distribution of the
distances between nodes randomly distributed in a bounded
domain. As no such result exists in the literature, we make progress by
obtaining the joint distribution of the distances between three nodes confined
in a disk in . This enables the calculation of the probability
distribution and entropy of a three-node graph. For arbitrary , we derive a
series of upper bounds on the graph entropy; in particular, the bound involving
the entropy of a three-node graph is tighter than the existing bound which
assumes distances are independent. Finally, we provide numerical results on
graph connectedness and the tightness of the derived entropy bounds.Comment: submitted to the IEEE International Symposium on Information Theory
201
Quantifying Link Stability in Ad Hoc Wireless Networks Subject to Ornstein-Uhlenbeck Mobility
The performance of mobile ad hoc networks in general and that of the routing
algorithm, in particular, can be heavily affected by the intrinsic dynamic
nature of the underlying topology. In this paper, we build a new
analytical/numerical framework that characterizes nodes' mobility and the
evolution of links between them. This formulation is based on a stationary
Markov chain representation of link connectivity. The existence of a link
between two nodes depends on their distance, which is governed by the mobility
model. In our analysis, nodes move randomly according to an Ornstein-Uhlenbeck
process using one tuning parameter to obtain different levels of randomness in
the mobility pattern. Finally, we propose an entropy-rate-based metric that
quantifies link uncertainty and evaluates its stability. Numerical results show
that the proposed approach can accurately reflect the random mobility in the
network and fully captures the link dynamics. It may thus be considered a
valuable performance metric for the evaluation of the link stability and
connectivity in these networks.Comment: 6 pages, 4 figures, Submitted to IEEE International Conference on
Communications 201
Topological Interference Management with Alternating Connectivity
The topological interference management problem refers to the study of the
capacity of partially connected linear (wired and wireless) communication
networks with no channel state information at the transmitters (no CSIT) beyond
the network topology, i.e., a knowledge of which channel coefficients are zero
(weaker than the noise floor in the wireless case). While the problem is
originally studied with fixed topology, in this work we explore the
implications of varying connectivity, through a series of simple and
conceptually representative examples. Specifically, we highlight the
synergistic benefits of coding across alternating topologies
Design of a multiple bloom filter for distributed navigation routing
Unmanned navigation of vehicles and mobile robots can be greatly simplified by providing environmental intelligence with dispersed wireless sensors. The wireless sensors can work as active landmarks for vehicle localization and routing. However, wireless sensors are often resource scarce and require a resource-saving design. In this paper, a multiple Bloom-filter scheme is proposed to compress a global routing table for a wireless sensor. It is used as a lookup table for routing a vehicle to any destination but requires significantly less memory space and search effort. An error-expectation-based design for a multiple Bloom filter is proposed as an improvement to the conventional false-positive-rate-based design. The new design is shown to provide an equal relative error expectation for all branched paths, which ensures a better network load balance and uses less memory space. The scheme is implemented in a project for wheelchair navigation using wireless camera motes. © 2013 IEEE
A mosaic of eyes
Autonomous navigation is a traditional research topic in intelligent robotics and vehicles, which requires a robot to perceive its environment through onboard sensors such as cameras or laser scanners, to enable it to drive to its goal. Most research to date has focused on the development of a large and smart brain to gain autonomous capability for robots. There are three fundamental questions to be answered by an autonomous mobile robot: 1) Where am I going? 2) Where am I? and 3) How do I get there? To answer these basic questions, a robot requires a massive spatial memory and considerable computational resources to accomplish perception, localization, path planning, and control. It is not yet possible to deliver the centralized intelligence required for our real-life applications, such as autonomous ground vehicles and wheelchairs in care centers. In fact, most autonomous robots try to mimic how humans navigate, interpreting images taken by cameras and then taking decisions accordingly. They may encounter the following difficulties
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