Efficient Location Aware Protocol for Multi-UAV Networks

Abstract

Unmanned aerial vehicles (UAVs), generally known as drones, have gained considerable attention from the research community and business organizations over the past few years. Indeed, UAVs are being widely deployed to provide on-demand wireless coverage in extreme conditions such as disaster-prone areas and delivery of essential products such as medicines and food during rescue operations. For this purpose, multiple UAVs can form a web of drones, geo-distributed across a large coverage area to perform ad hoc and distributed operations quickly and cost-e↵ectively. The UAVs can also collaborate and coordinate with other cutting edge technologies such as Software Defined Networking (SDN), Internet of Things (IoT) and Blockchain to realization various futuristic on-demand consumer applications and service across the smart city. The popular UAV-based applications can be categorized into domains like UAV-assisted data relaying, UAV-assisted monitoring and data collection and UAV-assisted product delivery. Despite various advantages of using UAVs, there are associated challenges while utilizing them in on-demand applications. The key challenges are deployment, data o✏oading and bandwidth, power consumption, energy efficiency, accuracy, latency etc. Thus, it is consequential to formalize an efficient solution, which can provide sustainable connectivity in drone networks with efficient control as well as provisioning of the high Quality of Service (QoS). So, far the drone to drone and drone to ground communication, the work is presented on four major challenges: (i) collision (ii) network congestion (iii) energy consumption (iv) location-aware and Quality of Service (QoS) (v) energy optimization of UAVs at the time of charging, discharging, iii iv and information transmission. To resolve the above mentioned challenges, the task has been accomplished in this research work with three di↵erent approaches. The first approach presents a Medium Access Control (MAC) protocol is proposed that utilizes the firefly optimization algorithm for operating the timing cycle of the network. To support the proposed protocol, three algorithms are designed to accomplish the challenges related to collision, network congestion, and energy consumption. The first algorithm deals with collision avoidance and is designed on the basis of the light intensity property of the firefly optimization. The second algorithm handles the network congestion by controlling the size of the congestion window. The third algorithm computes the nearby optimal route with minimum energy consumption along with the QoS requirements. The performance analysis suggests that the proposed approach provides an efficient congestion-free, collisionfree, and energy efficient MAC with signaling quality amended up to 59.04% along with 80.1% conservation of energy. The second approach focused on QoS provisioning in a multi-UAV ecosystem. The parameters considered for the improvement of QoS provisioning are network throughput, end-to-end delay, and handover latency. Thus, the proposed approach works in two phases. In the first phase, an opportunistic o✏oading scheme based on SDN adaptive controller is proposed to handle congestion issues in the network. The SDN controller automatically reacts to the suspicious change of the network state and thereby maintains a high level of security. The second phase focused on the network selection to be coordinated by priority manager and network manager. Priority manager helps in deciding the data priority to be o✏oaded, whereas the network managers provide the information of the available uncongested heterogeneous network so that the SDN controller can perform data o✏oading. The proposed scheme minimizes the handover latency upto 47% in comparison to other schemes. In addition, the proposed scheme increases the network throughput upto 14% and minimizes the end-to-end delay upto 25%. v Finally, the third approach considered the challenge of energy optimization. In UAVs network, the charging of UAVs batteries while performing their operations without being grounded, referred as energy replenishment is one of the major issues when they are deployed in civilian applications. For the purpose, an opportunistic SDN-enabled wireless energy charging scheme is proposed. The proposed solution of the energy charging system works in two parts, (i) the first part is solar energy harvesting model using solar cells, and (ii) the second part is wireless charging of UAVs through geo-located charging points in a grid-based layout. The solar energy harvesting model helps the UAVs to replenish their batteries during the day time, while the wireless charging model perfectly works in the night time or in extreme conditions. The proposed wireless energy-charging scheme helps to elongate the flight time of UAVs and sustain the flight whenever the battery state of charge is low.