A Coverage Inference Protocol for Wireless Sensor Networks

Abstract

Abstract-After a wireless sensor network (WSN) is deployed, sensor nodes are usually left unattended for a long period of time.There is an inevitable devolution of the connected coverage of the WSN due to battery exhaustion of sensor nodes, intended physical destruction attacks on sensor nodes, unpredictable node movement by physical means like wind, and so on. It is, therefore, critical that the base station (BS) learns in real time how well the WSN performs the given sensing task (i.e., what is the current connected coverage) under a dynamically changing network topology. In this paper, we propose a coverage inference protocol (CIP), which can provide the BS an accurate and in-time measurement of the current connected coverage in an energy-efficient way. Especially, we show that the scheme called BOND, which our CIP requires to be implemented on each sensor node, enables each node to locally self-detect whether it is a boundary node with the minimal communication and computational overhead. The BOND can also be exploited to seamlessly integrate multiple functionalities with low overhead. Moreover, we devise extensions to CIP that can tolerate location errors and actively predict the change of the connected coverage based on residual energy of sensor nodes.

A Coverage Hole Healing Strategy with Awareness of Data Delivery Time in Wireless Sensor Networks

“…The authors of [23] proposed the boundary node detection scheme, which uses the LVP (localized Voronoi polygons) algorithm to find border nodes. By using the algorithm, the nodes will know whether they are a border node or not by neighboring nodes' information only, and these nodes will transmit their status information to the sink.…”

Connected Coverage Optimization for Sensor Scheduling in Wireless Sensor Networks

“…The works in [20] and [21] used a Voronoi Polygon as a partition between the sensors. The authors proposed the BOND algorithm based on two novel geometric concepts: the Localised Voronoi Polygon (LVP) and the Tentative LVP (TLVP).…”

Fast identification of the missing tags in a large RFID system

“…The optimal number and deployment of RFID readers depend on the size and shape of the monitored region, the number of tags, the minimum transmission range among the tags, the actual coverage requirement (say, -coverage), and other factors. This problem can be solved by referring to the existing rich literature on sensor network coverage (see [4] and the references therein) and is orthogonal to our work in this paper.…”