13,265 research outputs found
Unmanned Ground Vehicle navigation and coverage hole patching in Wireless Sensor Networks
This dissertation presents a study of an Unmanned Ground Vehicle (UGV) navigation and coverage hole patching in coordinate-free and localization-free Wireless Sensor Networks (WSNs). Navigation and coverage maintenance are related problems since coverage hole patching requires effective navigation in the sensor network environment. A coordinate-free and localization-free WSN that is deployed in an ad-hoc fashion and does not assume the availability of GPS information is considered. The system considered is decentralized and can be self-organized in an event-driven manner where no central controller or global map is required.
A single-UGV, single-destination navigation problem is addressed first. The UGV is equipped with a set of wireless listeners that determine the slope of a navigation potential field generated by the wireless sensor and actuator network. The navigation algorithm consists of sensor node level-number assignment that is determined based on a hop-distance from the network destination node and UGV navigation through the potential field created by triplets of actuators in the network. A multi-UGV, multi-destination navigation problem requires a path-planning and task allocation process. UGVs inform the network about their proposed destinations, and the network provides feedback if conflicts are found. Sensor nodes store, share, and communicate to UGVs in order to allocate the navigation tasks. A special case of a single-UGV, multi-destination navigation problem that is equivalent to the well-known Traveling Salesman Problem is discussed.
The coverage hole patching process starts after a UGV reaches the hole boundary. For each hole boundary edge, a new node is added along its perpendicular bisector, and the entire hole is patched by adding nodes around the hole boundary edges.
The communication complexity and present simulation examples and experimental results are analyzed. Then, a Java-based simulation testbed that is capable of simulating both the centralized and distributed sensor and actuator network algorithms is developed. The laboratory experiment demonstrates the navigation algorithm (single-UGV, single-destination) using Cricket wireless sensors and an actuator network and Pioneer 3-DX robot
Homology-based Distributed Coverage Hole Detection in Wireless Sensor Networks
Homology theory provides new and powerful solutions to address the coverage
problems in wireless sensor networks (WSNs). They are based on algebraic
objects, such as Cech complex and Rips complex. Cech complex gives accurate
information about coverage quality but requires a precise knowledge of the
relative locations of nodes. This assumption is rather strong and hard to
implement in practical deployments. Rips complex provides an approximation of
Cech complex. It is easier to build and does not require any knowledge of nodes
location. This simplicity is at the expense of accuracy. Rips complex can not
always detect all coverage holes. It is then necessary to evaluate its
accuracy. This work proposes to use the proportion of the area of undiscovered
coverage holes as performance criteria. Investigations show that it depends on
the ratio between communication and sensing radii of a sensor. Closed-form
expressions for lower and upper bounds of the accuracy are also derived. For
those coverage holes which can be discovered by Rips complex, a homology-based
distributed algorithm is proposed to detect them. Simulation results are
consistent with the proposed analytical lower bound, with a maximum difference
of 0.5%. Upper bound performance depends on the ratio of communication and
sensing radii. Simulations also show that the algorithm can localize about 99%
coverage holes in about 99% cases
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
Coverage and Connectivity in Three-Dimensional Networks
Most wireless terrestrial networks are designed based on the assumption that
the nodes are deployed on a two-dimensional (2D) plane. However, this 2D
assumption is not valid in underwater, atmospheric, or space communications. In
fact, recent interest in underwater acoustic ad hoc and sensor networks hints
at the need to understand how to design networks in 3D. Unfortunately, the
design of 3D networks is surprisingly more difficult than the design of 2D
networks. For example, proofs of Kelvin's conjecture and Kepler's conjecture
required centuries of research to achieve breakthroughs, whereas their 2D
counterparts are trivial to solve. In this paper, we consider the coverage and
connectivity issues of 3D networks, where the goal is to find a node placement
strategy with 100% sensing coverage of a 3D space, while minimizing the number
of nodes required for surveillance. Our results indicate that the use of the
Voronoi tessellation of 3D space to create truncated octahedral cells results
in the best strategy. In this truncated octahedron placement strategy, the
transmission range must be at least 1.7889 times the sensing range in order to
maintain connectivity among nodes. If the transmission range is between 1.4142
and 1.7889 times the sensing range, then a hexagonal prism placement strategy
or a rhombic dodecahedron placement strategy should be used. Although the
required number of nodes in the hexagonal prism and the rhombic dodecahedron
placement strategies is the same, this number is 43.25% higher than the number
of nodes required by the truncated octahedron placement strategy. We verify by
simulation that our placement strategies indeed guarantee ubiquitous coverage.
We believe that our approach and our results presented in this paper could be
used for extending the processes of 2D network design to 3D networks.Comment: To appear in ACM Mobicom 200
Construction of the generalized Cech complex
In this paper, we introduce an algorithm which constructs the generalized
Cech complex. The generalized Cech complex represents the topology of a
wireless network whose cells are different in size. This complex is often used
in many application to locate the boundary holes or to save energy consumption
in wireless networks. The complexity of a construction of the Cech complex to
analyze the coverage structure is found to be a polynomial time
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