Energy and Trust-Aware Routing in Wireless Networks for Multimedia Applications
DOI:
https://doi.org/10.14738/aivp.123.16994Keywords:
Wireless networks, Multimedia applications, Weigh Utility-based Stratified Sampling (WUSS), Hybrid Energy Efficient Distribution (HEED) with Whale Optimization Algorithm (WOA), Improved BlowFish Algorithm (IBFA), Bilateral Floyd – Warshall algorithmAbstract
With rapid proliferation of wireless communication technologies and increasing demand for multimedia applications, efficient routing in wireless networks has become critical research area. Energy usage control and data exchange are key in these networks. Due to sensor node resource constraints, wireless networks are subject to security threats. So, energy-aware trust-based approaches are powerful for identifying node behaviour and providing wireless network security. This paper presents a novel approach that integrates energy and trust considerations into the routing process to enhance the performance of multimedia applications in wireless networks. This multifaceted approach aims to establish a comprehensive framework that encompasses energy efficiency, trust, data security, path optimization, and superior multimedia streaming quality within wireless networks. This study encompasses the innovative Cluster formation technique by utilizing Weigh Utility-based Stratified Sampling (WUSS), facilitates efficient node clustering, leading to optimized resource allocation and energy efficiency. The integration of Hybrid Energy Efficient Distribution (HEED) with Whale Optimization Algorithm (WOA) for Cluster Head Selection enhances energy balance and network longevity. Data Security is fortified through the utilization of the Improved BlowFish Algorithm (IBFA), safeguarding multimedia content during transmission. The Bilateral Floyd – Warshall algorithm is harnessed for optimal path selection, reducing latency and packet loss for high-quality multimedia delivery. Multimedia streaming involves both sensitive and non-sensitive data, prioritizing seamless streaming while upholding data security. To simulate the suggested research method, Python – 3.11.4 is utilized. The proposed approach is utilized using several performance metrics such as Delivery rate, Network lifetime, Throughput, Delay, Packet loss and Packet Delivery Ratio.
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