Lakshman Prasad

Functional characterization of fault tolerant integration in distributed sensor networks

Fault-tolerance is an important issue in network design because sensor networks must function in a dynamic, uncertain world. A functional characterization of the fault-tolerant integration of abstract interval estimates is proposed. This model provides a preliminary version for a general framework that is hoped to develop to address the general problem of fault-tolerant integration of abstract sensor estimates. A scheme for narrowing the width of the sensor output in a specific failure model is proposed and given a functional representation. The main distinguishing feature of the model over the original model of K. Marzullo (1989) is in reducing the width of the output interval estimate significantly in most cases where the number of sensors involved is large. >

Functional characterization of sensor integration in distributed sensor networks

Fault-tolerance is an important issue in network design because sensor networks must function in a dynamic, uncertain world. In this paper, the authors propose a functional characterization of the fault-tolerant integration of abstract interval estimates. This model provides a test bed for a general framework which the authors hope to develop to address the general problem of fault-tolerant integration of abstract sensor estimates. They further propose a scheme for narrowing the width of the sensor output in a specific failure model and give it a functional representation. The main distinguishing feature of the authors model over the original Marzullos model is in reducing the width of the output interval estimate significantly in most cases where the number of sensors involved is large.<<ETX>>

A general computational framework for distributed sensing and fault-tolerant sensor integration

Proposes an abstract framework to address the problem of fault-tolerant integration of information provided by multiple sensors. This paper presents a formal description of spatially distributed sensor networks, where i) clusters of sensors monitor (possible overlapping) regions of the environment; ii) sensors return measured values of a multidimensional parameter of interest; and iii) uncertainties associated with a sensor output are represented by a connected subset in the parameter space. A method to obtain interval estimates of components of the actual parameter vector is developed, wherein information from faulty sensors are filtered out. The problem addressed involves combining interval estimates of sensor outputs into a best intersection estimate of outputs. The sensor fault model used assumes most faults cluster in the neighborhood of the correct values. The procedure of this paper is superior to earlier work. To test the theoretical analysis of the framework proposed, we have developed a modular parameter-driven simulator SIMDSN for the fault-tolerant integration of abstract sensor interval estimates. The simulator uses the well-known Monte-Carlo technique to generate random correct and tamely faulty intervals. >

A note on the combinatorial structure of the visibility graph in simple polygons

Abstract Combinatorial structure of visibility is probably one of the most fascinating and interesting areas of engineering and computer science. The usefulness of visibility graphs in computational geometry and robotic navigation problems like motion planning, unknown-terrain learning, shortest-path planning, etc., cannot be overstressed. The visibility graph, apart from being an important data structure for storing and updating geometric information, is a valuable mathematical tool in probing and understanding the nature of shapes of polygonal and polyhedral objects. In this research we wish to initially focus our attention on a fundamental class of geometric objects. These geometric objects may be looked upon as building blocks for more complex geometric objects, and which offer an ideal balance between complexity and simplicity, namely simple polygons. A major theme of the proposed paper is the investigation of the combinatorial structure of the visibility graph. More importantly, the goals of this paper are: 1. (i) To characterize the visibility graphs of simple polygons by obtaining necessary and sufficient conditions a graph must satisfy to qualify for the visibility graph of a simple polygon 2. (ii) To obtain hierarchical relationships between visibility graphs of simple polygons of a given number of vertices by treating them as representing simple polygons that are deformations of one another. 3. (iii) To exploit the potential of complete graphs to be natural coordinate systems for addressing the problem of reconstructing a simple polygon from visibility graph. We intend to achieve this by defining appropriate “betweenness” relationships on points with respect to the edges of the complete graphs.

Fault-tolerant integration of abstract sensor estimates using multiresolution decomposition

This paper proposes a method of applying the idea of multiresolution to the problem of fault-tolerant integration of abstract sensor estimates when the number of sensors is very large and a large number of sensor faults are tame. We give an optimal O(N log N) algorithm, where N is the total number of sensors, which implements this idea efficiently.<<ETX>>

An asymptotic equality for the number of necklaces in a shuffle-exchange network

Abstract The search for efficient bounds for VLSI problems has spawned an increasingly important research area. In this paper, we derive an asymptotic equality for the number of necklaces in a shuffle-exchange network, and provide a formula for the number of necklaces of a given length. This symptotic equality for the number of necklaces is an extension to Ullmans result reported in [2].

A polynomial time algorithm for an exact encoding of space containing

We address the problem of collision free navigation of a point robot among polygonal obstacles in a bounded known terrain in two dimensional space. The obstacles could be convex or concave polygons. We consider a combinatorial approach to the problem and focus on partitioning the terrain into distinct regions and encoding these regions. We then build a region-graph whose nodes represent the regions and every pair of neighbouring regions (nodes) are connected by an edge. We propose an o(n 4) preprocessing algorithm to do this. This converts the problem of navigation from a source point to a destination point into a problem of finding a path in a planar graph from one of its nodes to another in O (n 2 log n) time. The shortest path is derivable in 0(n 4) time. The extension of the algorithm for three-dimensional space is also discussed.