Dynamic coverage in ad-hoc sensor networks

Ad-hoc networks of sensor nodes are in general semi-permanently deployed. However, the topology of such networks continuously changes over time, due to the power of some sensors wearing out, to new sensors being inserted into the network, or even due to designers moving sensors around during a network re-design phase (for example, in response to a change in the requirements of the network). In this paper, we address the problem of how to dynamically maintain two important measures on the quality of the coverage of a sensor network: the best-case coverage and worst-case coverage distances. We assume that the ratio between upper and lower transmission power of sensors is bounded by a polynomial of n, where n is the number of sensors, and that the motion of mobile sensors can be described as a low-degree polynomial function of time. We maintain a (1 + ε)-approximation on the best-case coverage distance and a (√2 + ε)-approximation on the worst-case coverage distance of the network, for any fixed ε > 0. Our algorithms have amortized or worst-case poly-logarithmic update costs. We are able to efficiently maintain the connectivity of the regions on the plane with respect to the sensor network, by extending the concatenable queue data structure to also serve as a priority queue. In addition, we present an algorithm that finds the shortest maximum support path in time O(n log n).