Narrow Results

Ensuring different types of coverage is an important problem in many wireless sensor applications. In this paper, we address the problem of maintaining support coverage in the presence of sensor failures. Given a placement of n sensors in an area A, and any two points i and f in A, the support value of any path between i and f is the maximum distance of any point on the path from its closest sensor. The path with the minimum support value is called the maximal support path. The support value of a path may increase if a sensor fails. Given a maximal support path with a support value ψ, we first present two centralized approximation algorithms that, on failure of a single sensor, compute a new path with a support value close to ψ by moving exactly one nearby sensor. The first algorithm assumes that the sensors are allowed to move in any direction, and the second one assumes that the sensors are constrained to move in any of the four directions east, west, north, and south. Both the support value for the new path computed and the movement necessary are shown to be within a constant-factor of the initial support value. We then show that even in case of multiple sensor failures, a new path with a bounded support value can be computed. Detailed simulation results are provided to show that the algorithms result in significant improvement in many cases in practice, and the improvements obtained are significantly better than the worst case bounds given by the analysis. We also discuss distributed implementations of the algorithms.

Sensor networks that can support time-critical operations pose challenging problems for tracking events of interest. We propose an architecture for a sensor network that autonomously adapts in real-time to data fusion requirements so as not to miss events of interest and provides accurate real-time mobile target tracking. In the proposed architecture, the sensed data is processed in an abstract space called Information Space and the communication between nodes is modeled as an abstract space called Network Design Space. The two abstract spaces are connected through an interaction interface called InfoNet, that seamlessly translates the messages between the two. The proposed architecture is validated experimentally on a laboratory testbed for multiple scenarios.