A Machine Learning-Driven Hybrid Routing Protocol for Robust VoIP in Wireless Mesh Networks
编号:226 访问权限:仅限参会人 更新:2026-02-19 13:51:02 浏览:40次 拓展类型2

报告开始:2025年12月29日 18:00(Asia/Amman)

报告时间:15min

所在会场:[S4] Track 4: Dedicated Technologies for Wireless Networks Track 6: Signal Processing for Wireless Communications Track 8: Communication and Networking Technologies for Smart Agriculture [S4] Track 4: Dedicated Technologies for Wireless NetworksTrack 6: Signal Processing for Wireless CommunicationsTrack 8: Communication and Networking Technologies for Smart Agriculture

暂无文件

摘要
Wireless Mesh Networks (WMNs) represent a class of decentralized, self-organizing wireless systems widely adopted for real-time communication and broadband access in heterogeneous environments. In WMNs, multiple mesh routers and client nodes collaborate to relay data across multi-hop links through wireless access points (WAPs). The distributed nature of WMNs enables robust connectivity without relying on centralized infrastructure, making them suitable for applications such as community broadband, disaster recovery, and industrial IoT. Despite their flexibility, WMNs suffer from significant latency and packet loss due to dynamic topologies, node mobility, and multi-hop data forwarding. As the number of nodes increases within a given coverage region, data hopping and link disruptions lead to degraded Quality of Service (QoS), particularly in Voice over Internet Protocol (VoIP) applications where delay and jitter directly affect speech quality. In such cases, if an intermediate node fails, data packets must reroute through alternative hops, increasing end-to-end delay and reducing packet delivery performance. To address these challenges, this study proposes a Hybrid Routing Protocol (HRP) designed to enhance VoIP performance in WMNs by integrating intelligent node selection and adaptive path optimization. The HRP operates through three major phases: (1) Active Node Selection (ANS) for optimized node deployment and coverage control; (2) Hopfield Neural Network (HNN) for predictive route selection based on learned network dynamics; and (3) Particle Swarm Optimization (PSO) for dynamic path recovery under uncertain link conditions. The proposed HRP is simulated under varying node densities and distances to evaluate its adaptability and reliability. Comparative performance analysis against conventional routing protocols demonstrates that HRP achieves superior packet delivery ratio (PDR), lower end-to-end delay, and higher throughput, making it an efficient routing solution for real-time VoIP applications over Wireless Mesh Networks.
关键词
Wireless Mesh Network, Hybrid Routing Protocol, VoIP, Packet Delivery Ratio, Quality of Service.
报告人
Movva Koteswara Kishore
Research Scholar GIET UNIVERSITY

稿件作者
Movva Koteswara Kishore GIET UNIVERSITY
MM Prasad Reddy GIET Uninversity
B Nancharaiah Usha Rama
发表评论
验证码 看不清楚,更换一张
全部评论
重要日期
  • 会议日期

    12月29日

    2025

    12月31日

    2025

  • 12月20日 2025

    初稿截稿日期

  • 12月31日 2025

    报告提交截止日期

  • 12月31日 2025

    注册截止日期

主办单位
国际科学联合会
承办单位
扎尔卡大学
历届会议
移动端
在手机上打开
小程序
打开微信小程序
客服
扫码或点此咨询