xinghuanlai Associate Professor

Supervisor of Doctorate Candidates

Supervisor of Master's Candidates

  

  • Education Level: PhD graduate

  • Professional Title: Associate Professor

  • Alma Mater: 英国诺丁汉大学

  • Supervisor of Doctorate Candidates

  • Supervisor of Master's Candidates

  • School/Department: 计算机与人工智能学院

  • Discipline:Communications and Information Systems
    Computer Science and Technology
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    Language: 中文

    Paper Publications

    Multi-objective Optimization for Network Resource Management in Heterogeneous Vehicular Networks

    DOI number:10.1109/WCNC.2019.8885961

    Journal:2019 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE (WCNC)

    Place of Publication:Marrakech, MOROCCO

    Abstract:Heterogeneous network integration is a promising technique to support efficient data services in vehicular networks. However, due to highly dynamics of vehicular mobility and heterogeneous performance of wireless interfaces, it is still challenging to design an efficient scheduling policy for information services in vehicular networks. In this paper, we propose a centralized service architecture for managing heterogeneous network resources. Particularly, we comprehensively investigate the heterogeneity of networks, as well as the diversity of service requests. On this basis, we formulate the heterogeneous network resource management (HNRM) problem as a multiple-objective problem, which aims at minimizing both the service delay and the network access cost simultaneously. Then, we propose a packet-encoding based multi-objective algorithm (PEMA), which consists of two components: packet encoding for data broadcast and multi-objective algorithm for network interface selection. Specifically, for improving bandwidth efficiency, we develop a multiple-packet encoding (MPE) technique to serve more requests simultaneously. For network selection, we propose a multi-objective evolutionary mechanism to further minimize both the service delay and the network access cost via population evolution. Finally, we give a comprehensive performance evaluation to demonstrate the superiority of PEMA under a wide range of scenarios.Heterogeneous network integration is a promising technique to support efficient data services in vehicular networks. However, due to highly dynamics of vehicular mobility and heterogeneous performance of wireless interfaces, it is still challenging to design an efficient scheduling policy for information services in vehicular networks. In this paper, we propose a centralized service architecture for managing heterogeneous network resources. Particularly, we comprehensively investigate the heterogeneity of networks, as well as the diversity of service requests. On this basis, we formulate the heterogeneous network resource management (HNRM) problem as a multiple-objective problem, which aims at minimizing both the service delay and the network access cost simultaneously. Then, we propose a packet-encoding based multi-objective algorithm (PEMA), which consists of two components: packet encoding for data broadcast and multi-objective algorithm for network interface selection. Specifically, for improving bandwidth efficiency, we develop a multiple-packet encoding (MPE) technique to serve more requests simultaneously. For network selection, we propose a multi-objective evolutionary mechanism to further minimize both the service delay and the network access cost via population evolution. Finally, we give a comprehensive performance evaluation to demonstrate the superiority of PEMA under a wide range of scenarios.

    Co-author:Penglin Dai,Kai Liu,Xiao Wu,Huanlai Xing,Victor Lee

    Document Code:10.1109/WCNC.2019.8885961

    ISSN No.:1525-3511

    Translation or Not:no

    Date of Publication:2019-04-19

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