Machine learning

Game theory

Chemistry

Network topology

Overhead (engineering)

Lyapunov function

Stability (learning theory)

Physics

Mathematical economics

Nonlinear system

Vehicular ad hoc network

Dissemination

Operating system

Computer science

Key distribution in wireless sensor networks

Wireless ad hoc network

Gene

Quantum mechanics

Mathematics

Wireless

Wireless network

Evolutionary game theory

Computer network

Topology control

Robustness (evolution)

Distributed computing

Cluster analysis

Biochemistry

Telecommunications

IEEE Transactions on Vehicular Technology

Discovering and maintaining efficient routes for data dissemination in vehicular ad hoc networks (VANETs) has proven to be a very challenging problem. Clustering is one of the control protocols used to provide efficient and stable routes for data dissemination. However, the rapid changes in network topology in VANETs creates frequent cluster reformation, which can seriously affect route stability. We propose a novel evolutionary game theoretic (EGT) framework to automate the clustering of nodes and nominations of cluster heads, to achieve cluster stability in VANETs. The equilibrium point is proven analytically and the stability is also tested using Lyapunov function. The performance of the proposed evolutionary game is empirically investigated with different cost functions using static and mobile scenarios. The simulation results demonstrate the effectiveness and robustness of our proposed EGT approach for different populations and speeds, thus reducing the overhead of frequent cluster reformation in VANETs.

An Evolutionary Game Theoretic Approach for Stable and Optimized Clustering in VANETs