Energy efficient device discovery for reliable communication in 5G-based IoT and BSNs using unmanned aerial vehicles

Abstract

Connectivity among real-world entities is one of the primary requirements of the upcoming Fifth Generation Public Private Partnership (5G-PPP). Both Internet of Things (IoT) and Body Sensor Networks (BSNs) are major applications of 5G networks. However, over-consumption of energy for device discovery, which includes registration, removal, querying, routing etc, quickly depletes the resources of a node, which may further influence the whole network. There are a number of approaches which provide energy efficient mechanisms for the selection of devices in a network operating with different types of nodes; however, these approaches are unable to maintain a high transmission capacity along with energy conservation and fault-tolerance. In this paper, an energy efficient approach for device discovery in 5G-based IoT and BSNs using multiple Unmanned Aerial Vehicles (UAVs) is presented. A functional architecture is proposed, which utilizes XML charts to perform device discovery on the basis of networks state cost and available energy. The significant gains achieved in energy consumption, end to end delays and packet loss show that our solution is capable of providing energy efficient device discovery with 78.4% reduction in the overall energy consumption compared to existing solutions. The advantage of UAVs in energy efficient networking is illustrated using numerical analysis which suggests 75% enhancement in the energy-asymptote of the existing networks.