Approximation Algorithm for Line Segment Coverage for Wireless Sensor Network

The coverage problem in wireless sensor networks deals with the problem of covering a region or parts of it with sensors. In this paper, we address the problem of covering a set of line segments in sensor networks. A line segment ` is said to be covered if it intersects the sensing regions of at least one sensor distributed in that region. We show that the problem of finding the minimum number of sensors needed to cover each member in a given set of line segments in a rectangular area is NP-hard. Next, we propose a constant factor approximation algorithm for the problem of covering a set of axis-parallel line segments. We also show that a PTAS exists for this problem.Comment: 16 pages, 5 figures

Localized Sensor Self-Deployment with Coverage Guarantee in Complex Environment

International audienceIn focused coverage problem, sensors are required to be deployed around a given point of interest (POI) with respect to a priority requirement: an area close to POI has higher priority to be covered than a distant one. A localized sensor self-deployment algorithm, named Greedy-Rotation-Greedy (GRG) [10], has recently been proposed for constructing optimal focused coverage. This previous work assumed obstacle-free environment and focused on theoretical aspects. Here in this paper, we remove this strong assumption, and extend GRG to practical settings. We equip GRG with a novel obstacle penetration technique and give it the important obstacle avoidance capability. The new version of GRG is referred to as GRG/OP. Through simulation, we evaluate its performance in comparison with plain GRG

Localized Sensor Self-Deployment with Coverage Guarantee in Complex Environment

International audienceIn focused coverage problem, sensors are required to be deployed around a given point of interest (POI) with respect to a priority requirement: an area close to POI has higher priority to be covered than a distant one. A localized sensor self-deployment algorithm, named Greedy-Rotation-Greedy (GRG) [10], has recently been proposed for constructing optimal focused coverage. This previous work assumed obstacle-free environment and focused on theoretical aspects. Here in this paper, we remove this strong assumption, and extend GRG to practical settings. We equip GRG with a novel obstacle penetration technique and give it the important obstacle avoidance capability. The new version of GRG is referred to as GRG/OP. Through simulation, we evaluate its performance in comparison with plain GRG

Sensor Networks Deployment Using Flip-Based Sensors

In this paper, we study the issue of mobility based sensor networks deployment. The distinguishing feature of our work is that the sensors in our model have limited mobilities. More specifically, the mobility in the sensors we consider is restricted to a flip, where the distance of the flip is bounded. Given an initial deployment of sensors in a field, our problem is to determine a movement plan for the sensors in order to maximize the sensor network coverage, and minimize the number of flips. We propose a minimum-cost maximum-flow based solution to this problem. We prove that our solution optimizes both the coverage and the number of flips. We also study the sensitivity of coverage and the number of flips to flip distance under different initial deployment distributions of sensors. We observe that increased flip distance achieves better coverage, and reduces the number of flips required per unit increase in coverage. However, such improvements are constrained by initial deployment distributions of sensors, due to the limitations on sensor mobility