Coding-Assisted broadcast scheduling via memetic computing in SDN-Based vehicular networks

Kai Liu, Liang Feng, Penglin Dai, Victor C.S. Lee, Sang Hyuk Son, Jiannong Cao

Research output: Journal article publicationJournal articleAcademic researchpeer-review

35 Citations (Scopus)


This paper embarks the first study on exploiting the synergy between vehicular caching and network coding for enhancing the bandwidth efficiency of data broadcasting in heterogeneous vehicular networks by presenting a service architecture that exercises the software defined network concept. In particular, we consider the scenario where vehicles request a set of information and they could be served via heterogeneous wireless interfaces, such as roadside units and base stations (BSs). We formulate a novel problem of coding-assisted broadcast scheduling (CBS), aiming at maximizing the broadcast efficiency for the limited BS bandwidth by exploring the synergistic effect between vehicular caching and network coding. We prove the NP-hardness of the CBS problem by constructing a polynomial-time reduction from the simultaneous matrix completion problem. To efficiently solve the CBS problem, we employ memetic computing, which is a nature inspired computational paradigm for tackling complex problems. Specifically, we propose a memetic algorithm, which consists of a binary vector representation for encoding solutions, a fitness function for solution evaluation, a set of operators for offspring generation, a local search method for solution enhancement, and a repair operator for fixing infeasible solutions. Finally, we build the simulation model and give a comprehensive performance evaluation to demonstrate the superiority of the proposed solution.

Original languageEnglish
Article number8048610
Pages (from-to)2420-2431
Number of pages12
JournalIEEE Transactions on Intelligent Transportation Systems
Issue number8
Publication statusPublished - Aug 2018


  • data broadcast
  • memetic algorithm
  • network coding
  • SDN-based vehicular network

ASJC Scopus subject areas

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications

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