Geographic Drone-based Route Optimization Approach for Emergency Area Ad-Hoc Network

Abstract

Wireless sensor Mobile ad hoc networks have excellent potential in moving and monitoring disaster area networks on real-time basis. The recent challenges faced in Mobile Ad Hoc Networks (MANETs) include scalability, localization, heterogeneous network, self-organization, and self-sufficient operation. In this background, the current study focuses on specially-designed communication link establishment for high connection stability of wireless mobile sensor networks, especially in disaster area network. Existing protocols focus on location-dependent communications and use networks based on typically-used Internet Protocol (IP) architecture. However, IP-based communications have a few limitations such as inefficient bandwidth utilization, high processing, less transfer speeds, and excessive memory intake. To overcome these challenges, the number of neighbors (Node Density) is minimized and high Mobility Nodes (Node Speed) are avoided. The proposed Geographic Drone Based Route Optimization (GDRO) method reduces the entire overhead to a considerable level in an efficient manner and significantly improves the overall performance by identifying the disaster region. This drone communicates with anchor node periodically and shares the information to it so as to introduce a drone-based disaster network in an area. Geographic routing is a promising approach to enhance the routing efficiency in MANET. This algorithm helps in reaching the anchor (target) node with the help of Geographical Graph-Based Mapping (GGM). Global Positioning System (GPS) is enabled on mobile network of the anchor node which regularly broadcasts its location information that helps in finding the location. In first step, the node searches for local and remote anticipated Expected Transmission Count (ETX), thereby calculating the estimated distance. Received Signal Strength Indicator (RSSI) results are stored in the local memory of the node. Then, the node calculates the least remote anticipated ETX, Link Loss Rate, and information to the new location. Freeway Heuristic algorithm improves the data speed, efficiency and determines the path and optimization problem. In comparison with other models, the proposed method yielded an efficient communication, increased the throughput, and reduced the end-to-end delay, energy consumption and packet loss performance in disaster area networks.