Detecting Gaps and Voids in WSNs and IoT Networks: the Angle-based Method

Abstract

A random deployment of Wireless Sensor Networks (WSNs) is often the basic structure used in the context of fire forest detection, military applications or any situation where the zone-of-interest is not accessible by humans. The main problematic in this kind of deployment is the formation of gaps or voids, which represent a zone which is not covered in the network. This reduces significantly its Quality of Service and can lead to serious problems, like a non-detected starting fire, the presence of unexpected persons or attacks, etc. Therefore, detecting zones that are not covered by the WSN is of great importance. In this paper, we present a new method allowing to detect gaps and voids in WSNs or in IoT networks by using some characteristics of the angles of the polygon formed by the boundary as determined by the D-LPCN algorithm. These angles can be interior or exterior. Characterizing the angles of the polygon formed by these boundary nodes allows to specify whether this boundary is a gap or a void, in case where the obtained polygon is interior. Since D-LPCN is fault-tolerant, the simulation results show that it is possible to use it for the detection of faulty nodes and intrusion