4.7 Article

A Mobility-Aware Vehicular Caching Scheme in Content Centric Networks: Model and Optimization

期刊

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
卷 68, 期 4, 页码 3100-3112

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2019.2899923

关键词

Vehicular caching; convex optimization; nonlinear fractional programming; Lyapunov optimization; energy efficiency

资金

  1. National Natural Science Foundation of China [U1801266, 61571350, 61601344]
  2. Key Research and Development Program of Shaanxi [2017KW-004, 2017ZDXM-GY-022, 2018ZDXM-GY-038, 2018ZDCXL-GY-04-02]

向作者/读者索取更多资源

Edge caching is being explored as a promising technology to alleviate the network burden of cellular networks by separating the computing functionalities away from cellular base stations. However, the service capability of existing caching scheme is limited by fixed edge infrastructure when facing the uncertainties of users' requests and locations. The vehicular caching, which uses the moving vehicles as cache carriers, is regarded as an efficient method to solve the above problem. This paper studies the effectiveness of vehicular caching scheme in content centric networks by developing optimization model toward the minimization of network energy consumption. Particularly, we model the interactions between caching vehicles and mobile users as a two-dimensional Markov process, in order to characterize the network availability of mobile users. Based on the developed model, we propose an online vehicular caching design by optimizing network energy efficiency. Specifically, the problem of caching decision making is first formulated as a fractional optimization model, toward the optimal energy efficiency. Using nonlinear fractional programing technology and Lyapunov optimization theory, we derive the theoretical solution for the optimization model. An online caching algorithm to enable the optimal vehicular caching is developed based on the solution. Finally, extensive simulations are conducted to examine the performance of our proposal. On comparison, our online caching scheme outperforms the existing scheme in terms of energy efficiency, hit ratio, cache utilization, and system gain.

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