A Game Theoretic Approach for Mobility Prediction Clustering in Unmanned Aerial Vehicle Networks

• Published in: IEEE transactions on vehicular technology Vol. 68; no. 10; pp. 9963 - 9973
• Main Authors: Xing, Na, Zong, Qun, Dou, Liqian, Tian, Bailing, Wang, Qing
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.10.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Clustering; Clustering algorithms; Coalition game; Game theory; Games; Link subsistence probability; Network topologies; Signal processing algorithms; Switch operation; Switches; Switching theory; Task analysis; Unmanned aerial vehicles
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2019.2936894

Unmanned aerial vehicle (UAV) swarms have attracted great interests in numerous civil and military scenarios due to their flexible deployment and mobility. The increased network size poses a challenge for the network scalability. Clustering as an effective scheme, is able to provide efficient communication and network performance. In order to adapt to the change of network topology, the link subsistence probability is used to evaluate the mobility of UAVs. However, the UAVs usually perform tasks collaboratively, which leads to their movements are typically group-based. To this end, a coalition game theoretic framework is proposed to cluster UAVs into coalitions in a distributed autonomous manner, based on the group and the mobility information. The proposed game allows the UAVs with the same group, as much as possible, into one coalition under some constraints, such as cluster size and cluster diameter. To solve the game, each UAV makes its decision whether to switch based on the coalition value. Finally, some comparisons are provided to illustrate the efficiency of the proposed algorithm.