Work place: Department of Electronics and Computer Engineering, Vignan’s Institute of Information Technology, Visakhapatnam – 530049, Andhra Pradesh, India
E-mail: drhdevanna@gmail.com
Website:
Research Interests: Cognitive architecture
Biography
Associate Professor Dr. H. Devanna, Department of Electronics and Computer Engineering, Vignan’s Institute of Information Technology (Autonomous), Visakhapatnam, Andhra Pradesh, India. Major interests: Adhoc Networking; Digital Communications; MIMO Systems; Software Defined Radio; Cognitive Radio Communication.
By B. Nancharaiah D. Rajendra Prasad H. Devanna Balamuralikrishna Potti Sreechandra Swarna
DOI: https://doi.org/10.5815/ijcnis.2025.01.02, Pub. Date: 8 Feb. 2025
Data packets in Wireless Mesh Networks (WMNs) are routed across several nodes in a multi-hop fashion. The Quality of Service (QoS), seamless connectivity, reliability, and scalability of Wireless Mesh Networks are all significantly impacted by routing approaches. Routing protocols should enforce the fair utilization of resources i.e. bandwidth or channel among network nodes irrespective of their spatial location from the Gateway. The two-hop or multi-hop nodes in wireless mesh networks experience resource starvation due to the functioning of the MAC protocol and TCP/TP networking protocol. The Starvation issue has a significant impact on the QoS requirements of wireless mesh networks. It is known that using appropriate scheduling techniques in network planning substantially minimizes starvation. To reduce the starving of resources to the multi-hop network nodes, novel optimized routing algorithms have been proposed and implemented in this work. To address the starvation, a GA-based cross-layer optimized scheduling method that operates at the MAC and Network layers is implemented. A hybrid approach that combines the features of the Genetic Algorithm (GA) and Gravitational Search Algorithm (GSA) is also implemented to solve the local minimum problem in GA. Results show that the suggested optimization methods greatly improve the fairness performance of wireless mesh networks.
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