D. Naga Ravikiran

Work place: Department of Electronics and Communication Engineering, Chalapathi Institute of Technology, Guntur, Andhra Pradesh - 522016, India

E-mail: nagaravikiran.phd@gmail.com

Website: https://orcid.org/0009-0007-8707-4609

Research Interests:

Biography

Dr. D. Naga Ravi Kiran earned his B.E. in Electronics and Communication Engineering from M.S. University, Tirunelveli, an M.E. in Digital Communication and Network Engineering from Anna University, and a Ph.D. in Wireless Sensor Networks from RTM Nagpur University in 2021. He also completed an AICTE QIP postgraduate certification in “From AI to Generative AI” from IIIT Allahabad. With over 22 years of teaching experience and more than 12 years of research experience, he is currently serving as Professor and Head of the Department of Electronics and Communication Engineering at Chalapathi Institute of Technology, Guntur. His research interests include wireless sensor networks, IoT, artificial intelligence, machine learning, computer vision, VLSI design, secure communications, and intelligent healthcare and transportation systems. He has published research papers, conference articles, and book chapters, and has filed patents in reinforcement learning-based spectrum allocation and quantum-inspired big-data processing. He received the NPTEL Discipline Star Award in 2026 and is a Life Member of ISTE and a professional member of IEEE.

Author Articles
QoS-Aware VoIP Support in WMNs via PSO-Based Multi-Level Node Monitoring

By Appala Raju Uppala D. Naga Ravikiran M. Koteswara Rao Srinivasa Rao Thamanam Gangolu Rajesh K. Sudha Rani

DOI: https://doi.org/10.5815/ijwmt.2026.04.06, Pub. Date: 8 Aug. 2026

Wireless Mesh Networks (WMNs) provide low-cost, self-organizing and self-healing connectivity, but multi-hop interference, hidden-node effects and unbalanced load make delay-sensitive Voice over Internet Protocol (VoIP) communication difficult to support. This paper presents a Particle Swarm Optimization (PSO)-driven node monitoring and traffic scheduling framework for QoS-aware VoIP in WMNs. In the revised method, multi-level monitoring is explicitly defined through three measurable levels: node-state monitoring (identifier, residual energy and queue occupancy), link-quality monitoring (delivery probability, loss, delay and interference), and traffic/QoS monitoring (VoIP classification and priority scheduling). These normalized features are combined in a dimensionally consistent PSO fitness function that jointly maximizes packet delivery ratio and residual energy while minimizing delay, packet loss and hop count. A MATLAB-based discrete-event simulation was conducted for WMNs with 50-300 nodes, bidirectional CBR/UDP VoIP flows, IEEE 802.11 CSMA/CA access and common channel/interference assumptions. Under the modeled conditions, the proposed PSO-MLNM-EPDR method achieved 97.7-98.8% packet delivery ratio, compared with 94.1-95.2% for RAAOR-WMN and 92.7-93.7% for FDOE-WMN, while keeping one-way delay within 7.4-8.6 ms. The study is limited to controlled simulation settings without mobility or field deployment; therefore, future work should validate the method under realistic traffic bursts, mobility and heterogeneous radio environments.

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