4.7 Article

A Joint Multi-Criteria Utility-Based Network Selection Approach for Vehicle-to-Infrastructure Networking

期刊

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TITS.2017.2778939

关键词

Heterogeneous wireless networks; energy efficiency; network selection; handover decision making; vehicle-to-infrastructure networking

资金

  1. National Natural Science Foundation of China [61571104, 61071124]
  2. General Project of Scientific Research of the Education Department of Liaoning Province [L20150174]
  3. Program for New Century Excellent Talents in University [NCET-11-0075]
  4. Fundamental Research Funds for the Central Universities [ZYGX2017KYQD170, N150402003, N120804004, N130504003]
  5. State Scholarship Fund [201208210013]

向作者/读者索取更多资源

The emerging technologies for connected vehicles have become hot topics. In addition, connected vehicle applications are generally found in heterogeneous wireless networks. In such a context, user terminals face the challenge of access network selection. The method of selecting the appropriate access network is quite important for connected vehicle applications. This paper jointly considers multiple decision factors to facilitate vehicle-to-infrastructure networking, where the energy efficiency of the networks is adopted as an important factor in the network selection process. To effectively characterize users' preference and network performance, we exploit energy efficiency, signal intensity, network cost, delay, and bandwidth to establish utility functions. Then, these utility functions and multi-criteria utility theory are used to construct an energy-efficient network selection approach. We propose design strategies to establish a joint multi-criteria utility function for network selection. Then, we model network selection in connected vehicle applications as a multi-constraint optimization problem. Finally, a multi-criteria access selection algorithm is presented to solve the built model. Simulation results show that the proposed access network selection approach is feasible and effective.

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