Adaptive Framework for Optimizing Blockchain Node Placement and VNF Allocation in IOV Networks

DOI

10.2991/978-94-6463-858-5_154How to use a DOI?

Keywords

IoV; Block chain; VNF Placement; Reinforcement Learning; Genetic Algorithms; Network Traffic; Resource Allocation; Failure Recovery

Abstract

Vehicles in IoV networks share data, but network congestion, unpredictable traffic, and resource limits create problems. Managing blockchain nodes and VNF placement in real-time is difficult. This study proposes ABV-IoV, a framework that allocates blockchain nodes and VNFs dynamically, considering traffic load, bandwidth, and failure recovery. The framework consists of three layers. The Edge Layer processes data near vehicles. The Blockchain Layer places blockchain nodes based on real-time network conditions. The Core Network Layer distributes data and resources efficiently. The Dynamic VNF Placement Engine applies Markov Decision Process (MDP) reinforcement learning to adjust VNF locations. The Blockchain Node Allocation Unit uses genetic algorithms to reduce delay and balance resource use. Simulations with NS-3, Mininet, SimBlock, and Veins compare ABV-IoV, GRL-SFT, and VNF-PRA under different traffic conditions. The results show that ABV-IoV maintains lower latency, processes more data, and improves resource use compared to the other models. It also recovers from failures faster, ensuring continuous operation. The study shows that dynamic blockchain and VNF allocation can help IoV networks handle traffic fluctuations and resource constraints. Future research can explore real-world testing and interoperability between multiple domains.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - B. Ramesh
AU  - Rajani Akula
PY  - 2025
DA  - 2025/11/04
TI  - Adaptive Framework for Optimizing Blockchain Node Placement and VNF Allocation in IOV Networks
BT  - Proceedings of International Conference on Computer Science and Communication Engineering (ICCSCE 2025)
PB  - Atlantis Press
SP  - 1876
EP  - 1888
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-858-5_154
DO  - 10.2991/978-94-6463-858-5_154
ID  - Ramesh2025
ER  -