Jul 2026· Signal Processing and Communications Applications Conference· pp. 1-4· 0 citations· 14 references
Abstract
End-to-end unmanned aerial vehicle networks suffer from overloading of central nodes due to shortest-path routing strategies. This study presents the CA-AODV approach, which integrates distributed eigenvector centrality computation into the AODV routing protocol. The proposed protocol employs a two-phase eigenvector computation mechanism, RREQ (Route Request) buffering for best-path selection, and a centrality-based link cost function to divert traffic away from central nodes. Simulation results conducted with OMNeT++ on a 50-node UAV network demonstrate that CA-AODV achieves up to %3.7 improvement in packet delivery ratio, up to %25.3 reduction in end-to-end delay, and %3.5 increase in sum rate compared to standard AODV under high traffic loads.
Simulation results demonstrate that the proposed protocol significantly minimizes traffic loss and guarantees a stable topology update time independent of timeout configurations, effectively maximizing network efficiency in multi-hop drone swarm operations.
Mihyun Kim, Hyunjun Ahn, Kijin Kim· Journal of the Korea Institu...· 0 citations
Wireless Mesh Networks (WMNs) are a key enabling technology for dynamic, infrastructure-limited IoT environments. The routing protocol is the central design choice in any WMN deployment because throughput, end-to-end delay, energy consumption and delivery reliability are directly affected by it. A systematic, simulatio...
Alá F. Khalifeh, Abdulla Ababneh, Iacovos I. Ioannou· IEEE Jordan Conference on Ap...· 0 citations
This paper presents a controller selection algorithm based on maximizing node betweenness centrality (MNB), which heuristically selects controller locations and improves control efficiency. Simulation results show that MNB reduces node configuration operations by 4.27% compared with random selection in a 100-node netwo...
Wenhong Liu, Zhihong Xiao, Min Liu et al.· International Conference on...· 0 citations
The paper introduces RML-ZEREM to solve existing limitations, which functions as a Reinforcement Learning (RL) based Zone-Based Leader-Aware Energy-Efficient Routing Protocol for MANETs, which serves next-generation MANET applications.
Rani Sahu, Babita Rathore· Journal of Intelligent Compu...· 0 citations
Simulation results indicate that HOA-MEPFL-CLCT-RP outperforms existing models in terms of Packet Delivery Ratio (PDR), energy efficiency, End-to-End Delay (E2D), and routing overhead.
Shaleena H, Sumangala K· International journal of com...· 0 citations
This work develops a multi-agent reinforcement learning (MARL) algorithm, termed Multi-Agent Proximal Policy Optimization with Dirichlet Modeling (MAPPO-DM), which follows the centralized-training-and-decentralized-execution framework and models continuous traffic-splitting actions using a Dirichlet distribution.
Zhenyu Zhao, Tian-Kui Zhang, Xiao-Xia Xu et al.· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.
