Energy-Efficient PCP Protocol for Probabilistic k- Coverage in Sensor Networks

Abstract

Wireless sensor networks are networks for collecting environment information in specific area using sensor nodes with low power. The important research problems in such sensor network applications are ensuring area coverage and maintaining the connectivity of the network. Area coverage means that nodes use their sensing modules to detect events occurring in the monitored area. Each sensor is assumed to have a sensing range, which depends on the phenomenon being sensed and the environment conditions. Maintaining the sensor network connected is also important because information about the detected events may need to be communicated to processing centers for possible actions. Connectivity is achieved by the radio communication modules installed in the sensors. Each sensor is assumed to have a communication range, which is totally different from the sensing range in general. The power consumption of nodes determines the lifetime of the wireless sensor network. Thus, the design of low-power node is very important. The sensors sense physical phenomena in different ways, and thus, are expected to have different sensing models. Even for the same sensor type, the sensing model may need to be changed in different environments. Designing and testing a different coverage protocol for each sensing model is indeed a costly task. To address this challenging task, we propose a new probabilistic coverage protocol (PCP) that could employ different sensing models. We show that PCP works with the common disk sensing model as well as probabilistic sensing models, with minimal changes. In this paper, the analysis and design of our coverage protocol can be extended to the probabilistic K-coverage case. K-coverage is needed in several sensor network applications to enhance reliability and accuracy of the network.