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  • 1.
    Englund, Cristofer
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), CAISR - Center for Applied Intelligent Systems Research. Viktoria Swedish ICT, Gothenburg, Sweden.
    Chen, Lei
    Viktoria Swedish ICT, Gothenburg, Sweden.
    Ploeg, Jeroen
    Netherlands Organization for Applied Scientific Research TNO, Hague, Netherlands.
    Semsar-Kazerooni, Elham
    Netherlands Organization for Applied Scientific Research TNO, Hague, Netherlands.
    Voronov, Alexey
    Viktoria Swedish ICT, Gothenburg, Sweden.
    Hoang Bengtsson, Hoai
    Viktoria Swedish ICT, Gothenburg, Sweden.
    Didoff, Jonas
    Viktoria Swedish ICT, Gothenburg, Sweden.
    The Grand Cooperative Driving Challenge 2016: Boosting the Introduction of Cooperative Automated Vehicles2016In: IEEE wireless communications, ISSN 1536-1284, E-ISSN 1558-0687, Vol. 23, no 4, p. 146-152Article in journal (Refereed)
    Abstract [en]

    The Grand Cooperative Driving Challenge (GCDC), with the aim to boost the introduction of cooperative automated vehicles by means of wireless communication, is presented. Experiences from the previous edition of GCDC, which was held in Helmond in the Netherlands in 2011, are summarized, and an overview and expectations of the challenges in the 2016 edition are discussed. Two challenge scenarios, cooperative platoon merge and cooperative intersection passing, are specified and presented. One demonstration scenario for emergency vehicles is designed to showcase the benefits of cooperative driving. Communications closely follow the newly published cooperative intelligent transport system standards, while interaction protocols are designed for each of the scenarios. For the purpose of interoperability testing, an interactive testing tool is designed and presented. A general summary of the requirements on teams for participating in the challenge is also presented.

  • 2.
    Kang, Jiawen
    et al.
    Guangdong University of Technology, Guangzhou, China & Guangdong Key Laboratory of IoT Information Technology, Guangzhou, China.
    Yu, Rong
    Guangdong University of Technology, Guangzhou, China & Guangdong Key Laboratory of IoT Information Technology, Guangzhou, China.
    Huang, Xumin
    Guangdong University of Technology, Guangzhou, China & Guangdong Key Laboratory of IoT Information Technology, Guangzhou, China.
    Jonsson, Magnus
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Bogucka, Hanna
    Poznan University of Technology, Poznan, Poland.
    Gjessing, Stein
    Zhang, Yan
    University of Oslo, Oslo, Norway & Simula Research Laboratory, Fornebu, Norway.
    Location privacy attacks and defenses in cloud-enabled internet of vehicles2016In: IEEE wireless communications, ISSN 1536-1284, E-ISSN 1558-0687, Vol. 23, no 5, p. 52-59Article in journal (Refereed)
    Abstract [en]

    As one of the promising branches of the Internet of Things, the cloud-enabled Internet of Vehicles (CE-IoV) is envisioned to serve as an essential data sensing, exchanging, and processing platform with powerful computing and storage capabilities for future intelligent transportation systems. The CE-IoV shows great promise for various emerging applications. In order to ensure uninterrupted and high-quality services, a vehicle should move with its own VM via live VM migration to obtain real-time location-based services. However, the live VM migration may lead to unprecedented location privacy challenges. In this article, we study location privacy issues and defenses in CE-IoV. We first present two kinds of unexplored VM mapping attacks, and thus design a VM identifier replacement scheme and a pseudonym-changing synchronization scheme to protect location privacy. We carry out simulations to evaluate the performance of the proposed schemes. Numerical results show that the proposed schemes are effective and efficient with high quality of privacy. © 2016 IEEE.

  • 3.
    Vinel, Alexey
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS).
    Breu, Jakob
    Mercedes-Benz Research & Development, Sindelfingen, Germany.
    Luan, Tom
    Xidian University, Xi'an, China.
    Hu, Honglin
    Shanghai Institute of Microsystem and Information Technology, Shanghai, China.
    Emerging Technology for 5G-Enabled Vehicular Networks2017In: IEEE wireless communications, ISSN 1536-1284, E-ISSN 1558-0687, Vol. 24, no 6, p. 12-12Article in journal (Refereed)
  • 4.
    Vinel, Alexey
    et al.
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Chen, Wen-Shyen Eric
    ProphetStor Data Services, Milpitas, CA, USA.
    Xiong, Neal N.
    Department of Business and Computer Science, Southwestern Oklahoma State University, Weatherford, Oklahoma, USA.
    Rho, Seungmin
    Department of Media Software at Sungkyul University, Anyang, South Korea.
    Chilamkurti, Naveen
    Department of Computer Science and Telecommunications, La Trobe University, Melbourne, Australia.
    Vasilakos, Athanasios V.
    Luleå University of Technology, Luleå, Sweden.
    Enabling wireless communication and networking technologies for the internet of things2016In: IEEE wireless communications, ISSN 1536-1284, E-ISSN 1558-0687, Vol. 23, no 5, p. 8-9, article id 7721735Article in journal (Refereed)
  • 5.
    Wang, Kun
    et al.
    Nanjing University of Posts and Telecommunications, Nanjing, China.
    Wang, Yunqi
    Nanjing University of Posts and Telecommunications, Nanjing, China.
    Hu, Xiaoxuan
    Nanjing University of Posts and Telecommunications, Nanjing, China.
    Sun, Yanfei
    Nanjing University of Posts and Telecommunications, Nanjing, China.
    Deng, Der-Jiunn
    National Changhua University of Education, Changhua City, Taiwan.
    Vinel, Alexey
    Halmstad University, School of Information Technology, Halmstad Embedded and Intelligent Systems Research (EIS), Centre for Research on Embedded Systems (CERES).
    Zhang, Yan
    University of Oslo, Oslo, Norway & Simula Research Laboratory, Fornebu, Norway.
    Wireless Big Data Computing in Smart Grid2017In: IEEE wireless communications, ISSN 1536-1284, E-ISSN 1558-0687, Vol. 24, no 2, p. 58-64Article in journal (Refereed)
    Abstract [en]

    The development of smart grid brings great improvement in the efficiency, reliability, and economics to power grid. However, at the same time, the volume and complexity of data in the grid explode. To address this challenge, big data technology is a strong candidate for the analysis and processing of smart grid data. In this article, we propose a big data computing architecture for smart grid analytics, which involves data resources, transmission, storage, and analysis. In order to enable big data computing in smart grid, a communication architecture is then described consisting of four main domains. Key technologies to enable big-data-aware wireless communication for smart grid are investigated. As a case study of the proposed architecture, we introduce a big-data- enabled storage planning scheme based on wireless big data computing. A hybrid approach is adopted for the optimization including GA for storage planning and a game theoretic inner optimization for daily energy scheduling. Simulation results indicate that the proposed storage planning scheme greatly reduce.

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