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Software-Defined Cooperative Data Sharing in Edge Computing Assisted 5G-VANET - 2019

Research Area:  Vehicular Ad Hoc Networks


It is widely recognized that connected vehicles have the potential to further improve the road safety, transportation intelligence and enhance the in-vehicle entertainment. By leveraging the 5G enabled Vehicular Ad hoc NETworks (VANET) technology, which is referred to as 5G-VANET, a flexible software-defined communication can be achieved with ultra-high reliability, low latency, and high capacity. Many enabling applications in 5G-VANET rely on sharing mobile data among vehicles, which is still a challenging issue due to the extremely large data volume and the prohibitive cost of transmitting such data using 5G cellular networks. This article focuses on efficient cooperative data sharing in edge computing assisted 5G-VANET. First, to enable efficient cooperation between cellular communication and Dedicated Short-Range Communication (DSRC), we first propose a software-defined cooperative data sharing architecture in 5G-VANET. The cellular link allows the communications between OpenFlow enabled vehicles and the Controller to collect contextual information, while the DSRC serves as the data plane, enabling cooperative data sharing among adjacent vehicles. Second, we propose a graph theory based algorithm to efficiently solve the data sharing problem, which is formulated as a maximum weighted independent set problem on the constructed conflict graph. Specifically, considering the continuous data sharing, we propose a balanced greedy algorithm, which can make the content distribution more balanced. Furthermore, due to the fixed amount of computing resources allocated to this software-defined cooperative data sharing service, we propose an integer linear programming based decomposition algorithm to make full use of the computing resources. Extensive simulations in NS3 and SUMO demonstrate the superiority and scalability of the proposed software-defined architecture and cooperative data sharing algorithms.

Author(s) Name:  Guiyang Luo; Haibo Zhou; Nan Cheng; Quan Yuan; Jinglin Li; Fangchun Yang; Xuemin Shen

Journal name:  IEEE Transactions on Mobile Computing

Conferrence name:  

Publisher name:  IEEE

DOI:  10.1109/TMC.2019.2953163

Volume Information:  ( Volume: 20, Issue: 3, March 1 2021) Page(s): 1212 - 1229