Innovative Models for Advanced Military IoT Communications using Improved Optimization with Connection-based Clustering Routing
G. Ramkumar
Abstract
Unmanned Aerial Vehicles (UAVs) are unmanned aircraft that fly without a human operator. Due to their maneuverability and accessibility, they are used in various applications such as aerial surveillance, delivery, and mapping and as well connected to the Internet of Things (IoT) devices. IoT includes smart home devices to industrial machinery, improving automation, and data-driven decision-making. Limited battery life limits the duration of work; sensitivity to weather conditions affects reliability. Data breaches are a potential outcome of security vulnerabilities, and the lack of interoperability makes it difficult to integrate diverse platforms. To overcome this drawback, this article introduced a novel approach called Improved Optimization with Connection-based Clustering Routing with MEC (IO-CBCM). IO-CBCM is used to enhance secure device-to-device communication in IoT networks through UAVs and Mobile Edge Computing (MEC) servers. The IO-CBCM framework is designed to optimize the Cluster Head (CH) selection and control cost reduction, while also improving overall system performance through particle swarm optimization (PSO) and increasing efficiency in Mobile Ad Hob Networks (MANETs). IO-CBCM-oriented clustering utilizes the system's structure to create clusters, which guarantees uninterrupted connectivity, decreases delay, maximizes energy savings, and boosts packet ratio. This holistic approach aims to strengthen network security, optimize resource allocation, and improve overall network performance in IoT environments. Here the performance analysis is calculated for the IO-CBCM model and compared with IDMB, ECDR, and SFTK with some parameters like false positive, clustering efficiency, packet delivery ratio, packet drop ratio, and throughput to achieve high performance.