TY - JOUR
T1 - A Mobility-Aware Vehicular Caching Scheme in Content Centric Networks
T2 - Model and Optimization
AU - Zhang, Yao
AU - Li, Changle
AU - Luan, Tom Hao
AU - Fu, Yuchuan
AU - Shi, Weisong
AU - Zhu, Lina
N1 - Publisher Copyright:
© 1967-2012 IEEE.
PY - 2019/4
Y1 - 2019/4
N2 - 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.
AB - 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.
KW - Lyapunov optimization
KW - Vehicular caching
KW - convex optimization
KW - energy efficiency
KW - nonlinear fractional programming
UR - http://www.scopus.com/inward/record.url?scp=85064721081&partnerID=8YFLogxK
U2 - 10.1109/TVT.2019.2899923
DO - 10.1109/TVT.2019.2899923
M3 - 文章
AN - SCOPUS:85064721081
SN - 0018-9545
VL - 68
SP - 3100
EP - 3112
JO - IEEE Transactions on Vehicular Technology
JF - IEEE Transactions on Vehicular Technology
IS - 4
M1 - 8643543
ER -