Selection and Orientation of Directional Sensors for Coverage Maximization

Abstract

Abstract-Sensor nodes may be equipped with a "directional" sensing device (such as a camera) which senses a physical phenomenon in a certain direction depending on the chosen orientation. In this article, we address the problem of selection and orientation of such directional sensors with the objective of maximizing coverage area. Prior works on sensor coverage have largely focused on coverage with sensors that are associated with a unique sensing region. In contrast, directional sensors have multiple sensing regions associated with them, and the orientation of the sensor determines the actual sensing region. Thus, the coverage problems in the context of directional sensors entails selection as well as orientation of sensors needed to activate in order to maximize/ensure coverage.In this article, we address the problem of selecting a minimum number of sensors and assigning orientations such that the given area (or set of target points) is kcovered (i.e., each point is covered k times). The above problem is NP-complete, and even NP-hard to approximate. Thus, we design a simple greedy algorithm that delivers a solution that k-covers at least half of the target points using at most M log(k|C|) sensors, where |C| is the maximum number of target points covered by a sensor and M is the minimum number of sensor required to k-cover all the given points. The above result holds for almost arbitrary sensing regions. We design a distributed implementation of the above algorithm, and study its performance through simulations. In addition to the above problem, we also look at other related coverage problems in the context of directional sensors, and design similar approximation algorithms for them.

The Issues of Coverage in Directional Sensor Network

“…In [5], the number of sensors and the orientation is studied and accordingly an algorithm is proposed to provide K-coverage. The solution given by [5] is that to cover half of the targets at most M*log (K |C|) where |C| is the maximum number of target points covered by a sensor and |M| is the minimum number of sensors required to K-cover All the given points.…”

“…The solution given by [5] is that to cover half of the targets at most M*log (K |C|) where |C| is the maximum number of target points covered by a sensor and |M| is the minimum number of sensors required to K-cover All the given points. Target may have incorporated priority; it might depend on the distance because due to the increasing distance the quality degrades.…”

Coverage in visual sensor networks with Pan-Tilt-Zoom cameras: The MaxFoV problem

“…Recall that the DISCRETE algorithm is typically used to enumerate the set of FoVs a camera can use [7], [8], [10], [16], [21]. In this section, we highlight limitations of using DISCRETE for PTZ cameras.…”

“…In VSNs, coverage has typically been considered for directional sensors (or pan-only cameras) [7], [10], [21] where each sensor can orient (pan) to cover k different sectors. The coverage problem assigns each camera to one sector to meet the coverage objective; for instance, to maximize the total targets covered [7], [8], [16], or to schedule cameras to allocate their time among different targets [11]. While PTZ cameras are able to provide superior coverage to pan-only cameras (or directional sensors), they introduce new challenges.…”

“…In coverage algorithms for directional sensors [2], [7], [8], [10], [16], [21], all discrete FoVs (sectors corresponding to the pan directions) are considered by coverage algorithms. We call this algorithm for generating feasible FoVs per camera the DISCRETE algorithm.…”