A Fast Cloud-Based Network Selection Scheme Using Coalition Formation Games in Vehicular Networks

• Published in: IEEE transactions on vehicular technology Vol. 64; no. 11; pp. 5327 - 5339
• Main Authors: Ke Xu, Kuang-Ching Wang, Amin, Rahul, Martin, Jim, Izard, Ryan
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-11-2015; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Cloud computing; coalition formation games; Distributed databases; Games; Global Positioning System; heterogeneous wireless networks; Measurement; network selection; Vehicles; vehicular networks; vertical handoff; heterogeneous wireless networks; vehicular networks; Coalition formation games; vertical handoff (VHO); network selection
• ISSN: 0018-9545; 1939-9359
• DOI: 10.1109/TVT.2014.2379953

Leveraging multiple wireless technologies and radio access networks (RANs), vehicles on the move have the potential to get robust connectivity and continuous service. To support the demands of as many vehicles as possible, an efficient and fast network selection scheme is critically important to achieve high performance and efficiency. So far, prior works have primarily focused on design of optimization algorithms and utility functions for either user or network performance. Most such studies do not address the complexities involved in the acquisition of needed information and the execution of algorithms, making them unsuitable for practical implementations in vehicles. This paper proposes a fast cloud-based network selection scheme for vehicular networks. By leveraging a compute cloud's abundant computing and data storage resources, vehicles can leverage wider scope network information for decision-making. Vehicles select best access networks through a coalition formation game approach. A one-iteration fast convergence algorithm is proposed to achieve the final state of coalition structure in the game. Through extensive simulation, the proposed network selection scheme was shown to balance system throughput and fairness with a built-in utility division rule of the framework. The algorithm efficiency showed eightfold enhancement over a conventional coalition formation algorithm. Such features validate the potential of implementation in practice.