CMHWN: coverage maximization of heterogeneous wireless network

Two of the main challenges in wireless sensor networks (WSNs) are connectivity and coverage. Connectivity keeps different nodes in the network linked and to exchange data. Coverage affects the efficiency of the operating sensors used in the network. This paper proposes a novel resilient incremental algorithm that improves the coverage of randomly distributed mobile devices within a heterogeneous or homogeneous environment. This algorithm guarantees connectivity by ensuring at least 2-connected neighbors for any device in the network. Results showed up to 89% coverage improvement in a heterogeneous environment and up to 99% coverage improvement in a homogeneous environment

MCCM: an approach for connectivity and coverage maximization

The internet of Things (IoT) has attracted significant attention in many applications in both academic and industrial areas. In IoT, each object can have the capabilities of sensing, identifying, networking and processing to communicate with ubiquitous objects and services. Often this paradigm (IoT) using Wireless Sensor Networks must cover large area of interest (AoI) with huge number of devices. As these devices might be battery powered and randomly deployed, their long-term availability and connectivity for area coverage is very important, in particular in harsh environments. Moreover, a poor distribution of devices may lead to coverage holes and degradation to the quality of service. In this paper, we propose an approach for self-organization and coverage maximization. We present a distributed algorithm for “Maintaining Connectivity and Coverage Maximization” called MCCM . The algorithm operates on different movable devices in homogeneous and heterogeneous distribution. It does not require high computational complexity. The main goal is to keep the movement of devices as minimal as possible to save energy. Another goal is to reduce the overlapping areas covered by different devices to increase the coverage while maintaining connectivity. Simulation results show that the proposed algorithm can achieve higher coverage and lower nodes’ movement over existing algorithms in the state of the art