TY - JOUR
T1 - A stackelberg game approach to proactive caching in large-scale mobile edge networks
AU - Zheng, Zijie
AU - Song, Lingyang
AU - Han, Zhu
AU - Li, Geoffrey Ye
AU - Poor, H. Vincent
N1 - Funding Information:
This work was supported in part by the National Natural Science Foundation of China under Grant 61625101, and in part by the U.S. National Science Foundation under Grants ECCS-1647198, CNS-1443894, CNS-1731017, CNS-1717454, CNS-1731424, CNS-1702850, and CNS-1646607.
Funding Information:
Manuscript received October 27, 2017; revised March 21, 2018 and May 14, 2018; accepted May 16, 2018. Date of publication May 30, 2018; date of current version August 10, 2018. This work was supported in part by the National Natural Science Foundation of China under Grant 61625101, and in part by the U.S. National Science Foundation under Grants ECCS-1647198, CNS-1443894, CNS-1731017, CNS-1717454, CNS-1731424, CNS-1702850, and CNS-1646607. The associate editor coordinating the review of this paper and approving it for publication was J. Zhang. (Corresponding author: Zijie Zheng.) Z. Zheng and L. Song are with the School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China (e-mail: zijie.zheng@pku.edu.cn; lingyang.song@pku.edu.cn).
Publisher Copyright:
© 2002-2012 IEEE.
PY - 2018/8
Y1 - 2018/8
N2 - Caching popular files in the storage of edge networks, namely edge caching, is a promising approach for service providers (SPs) to reduce redundant backhaul transmission to edge nodes (ENs). It is still an open problem to design an efficient incentive mechanism for edge caching in 5G networks with a large number of ENs and mobile users. In this paper, an edge network with one SP, a large number of ENs and mobile users with time-dependent requests is investigated. A convergent and scalable Stackelberg game for edge caching is designed. Specifically, the game is decomposed into two types of sub-games, a storage allocation game (SAG) and a number of user allocation games (UAGs). A Stackelberg game-based alternating direction method of multipliers (Stackelberg game-based ADMM) is proposed to solve either the SAG or each UAG in a distributed manner. Based on both analytical and simulation results, the convergence speed, the optimum of the entire game, and the amount of information exchange are linearly (or sublinearly) related to the network size, which indicates that this framework can potentially cope with large-scale caching problems. The proposed approach also requires less backhaul resource than the existed approaches.
AB - Caching popular files in the storage of edge networks, namely edge caching, is a promising approach for service providers (SPs) to reduce redundant backhaul transmission to edge nodes (ENs). It is still an open problem to design an efficient incentive mechanism for edge caching in 5G networks with a large number of ENs and mobile users. In this paper, an edge network with one SP, a large number of ENs and mobile users with time-dependent requests is investigated. A convergent and scalable Stackelberg game for edge caching is designed. Specifically, the game is decomposed into two types of sub-games, a storage allocation game (SAG) and a number of user allocation games (UAGs). A Stackelberg game-based alternating direction method of multipliers (Stackelberg game-based ADMM) is proposed to solve either the SAG or each UAG in a distributed manner. Based on both analytical and simulation results, the convergence speed, the optimum of the entire game, and the amount of information exchange are linearly (or sublinearly) related to the network size, which indicates that this framework can potentially cope with large-scale caching problems. The proposed approach also requires less backhaul resource than the existed approaches.
KW - Alternating direction of multipliers (ADMM)
KW - Large-scale networks
KW - Proactive caching
KW - Stackelberg game
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U2 - 10.1109/TWC.2018.2839111
DO - 10.1109/TWC.2018.2839111
M3 - Article
AN - SCOPUS:85047813035
SN - 1536-1276
VL - 17
SP - 5198
EP - 5211
JO - IEEE Transactions on Wireless Communications
JF - IEEE Transactions on Wireless Communications
IS - 8
M1 - 8369389
ER -