doi: 10.7763/IJCTE.2026.V18.1407
WREN-CR-VANET: Energy-efficient Cluster-based Routing for VANET
Sankara Srinivasa Rao Illapu1,*
,
Aswini Mula2 ,
Indu Dasari2 ,
Y. A. V. Lakshmi Prasanna2 ,
Sirisha Koribilli2 ,
Potnuru Siva2
- 1Computer Science and Engineering (Data Science) Department, Anil Neerukonda Institute of Technology & Sciences (ANITS), Visakhapatnam 531162, India
- 2Computer Science and Engineering Department, Gayatri Vidya Parishad Institute of Higher Learning and Research, Visakhapatnam 530048, India
- Manuscript receivedMay 7, 2026
- revisedJune 6, 2026
- acceptedAugust 28, 2026
- publishedNovember 10, 2026
Abstract
This paper presents Wren-based Cluster-based Routing for Vehicular Ad-Hoc Networks (WREN-CR-VANET), an energy-efficient, cluster-based routing framework for Vehicular Ad-Hoc Networks (VANETs) that jointly optimises cluster-head selection and multi-hop routing in a single, coupled hierarchical process. Unlike conventional schemes that treat clustering and routing as independent stages, the cluster topology produced during cluster-head selection directly defines the search space for route optimisation, making the two phases interdependent. Optimisation is performed by the Wren Metaheuristic Optimisation Algorithm (WMOA), a vehicular adaptation of the Superb Fairy-wren Optimisation Algorithm, whose adaptive exploration-exploitation mechanism delivers robust convergence with low parameter sensitivity relative to genetic, particle-swarm, and firefly-based methods. A stage-specific multi-objective fitness function guides cluster-head selection using residual energy, inter-vehicular distance, node degree, centrality, and cluster balance. At the same time, routing is optimised based on residual energy, communication distance, and link stability to preserve reliability during mobility. The framework is implemented in MATLAB and evaluated across vehicle densities ranging from 50 to 200. Compared with the Enhanced Cluster-based Lifetime Routing Protocol (ECBLTR), the Hybrid Genetic Firefly Algorithm (HGFA), and Bee-Foraging Learning Particle Swarm Optimisation (BFL-PSO), WREN-CR-VANET improves packet delivery ratio by 15.2%, reduces energy consumption by 21.3%, and extends network lifetime by 18.6%, with these improvements observed consistently across ten independent runs. Future work targets large-scale testbed deployment and security-aware extensions.
Keywords
- Vehicular Ad-Hoc Networks (VANET)
- WREN-CR-VANET
- superb fairy-wren optimisation algorithm
- energy-efficient clustering
- link stability-aware routing
- intelligent transportation systems
How to Cite
Sankara Srinivasa Rao Illapu, Aswini Mula, Indu Dasari, Y. A. V. Lakshmi Prasanna, Sirisha Koribilli, and Potnuru Siva, "WREN-CR-VANET: Energy-efficient Cluster-based Routing for VANET," International Journal of Computer Theory and Engineering, vol. 18, no. 4, pp. 274-286, 2026. https://doi.org/10.7763/IJCTE.2026.V18.1407
Copyright & License
Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).