Optimal Deployment and Scheduling with Directional Sensors for Energy-Efficient Barrier Coverage

In recent years, barrier coverage problem in directional sensor networks has been an interesting research issue. Most of the existing solutions to this problem aim to find as many barrier sets as possible to enhance coverage for the target area, which did not consider the power conservation. In this paper, we address the efficient sensor deployment (ESD) problem and energy-efficient barrier coverage (EEBC) problem for directional sensor networks. First, we describe a deployment model for the distribution of sensor locations to analyze whether a target area can be barrier covered. By this model, we examine the relationship between the probability of barrier coverage and network deployment parameters. Moreover, we model the EEBC as an optimization problem. An efficient scheduling algorithm is proposed to prolong the network lifetime when the target area is barrier covered. Simulation results are presented to demonstrate the performance of this algorithm. 1. Introduction Directional sensors, such as image sensors [1], video sensors [2] and infrared sensors [3], have been widely used to improve the performance of wireless sensor networks. Directional sensor has a limited angle of sensing range due to the technical constraints or cost considerations, which is different from omnidirectional sensor. Directional sensors may have several working directions and adjust their sensing directions during their operation. Power conservation is another important issue for directional sensor, just like omnidirectional sensor. Power consumption of sensor nodes has a great impact on the lifetime of sensor networks. Most directional sensors have limited power sources which are supplied by batteries. The batteries of sensors are not rechargeable due to the hostile or inaccessible environments in many scenarios. Due to the small size of existing batteries, sensor nodes cannot last as long as desired. Barrier coverage is an efficient way for many applications in directional sensor networks (DSNs), such as intrusion detection and border surveillance [4, 5]. There are two kinds of barrier coverage, that is, weak and strong [6], which are illustrated in Figure 1. Weak barrier coverage guarantees detections of intruders moving along congruent crossing paths, but it does not guarantee the detection of intruders moving along arbitrary crossing paths. Strong barrier coverage guarantees that no intruders can cross the region undetected no matter what crossing paths they choose. Constructing a strong barrier with directional sensors for a target region is a challenging problem. In this