A Social-Relation-Based Game Model for Distributed Clustering in Cooperative Wireless Networks

In this paper, a novel framework for cluster detection in cooperative wireless networks is proposed. This framework is modeled by a dynamic game with incomplete information, in which each player in the game aspires to improve its position in the network by forming cooperative groups. Instead of static systems, the attention we paid in this paper is highly dynamic networks, where the users' high mobility brings a huge challenge in clustering. In order to mitigate that impact, this paper is from the perspective of social relations to clustering, extracting users' social nature from their mobile patterns and designing distributed cluster strategy based on game model. The introduction of social nature with generally long-term characteristics makes clustering framework more predictive and stable. Simulations on real-world networks show that the proposed approach performs well in clustering in cooperative wireless networks.