A Game-Theoretic Analysis of Joint Mobile Edge Caching and Peer Content Sharing

被引:6
作者
Jiang, Changkun [1 ]
Gao, Lin [2 ,3 ,4 ]
Luo, Jingjing [2 ,3 ]
Zhou, Pan [5 ]
Li, Jianqiang [1 ]
机构
[1] Shenzhen Univ, Coll Comp Sci & Software Engn, Shenzhen 518060, Peoples R China
[2] Harbin Inst Technol, Sch Elect & Informat Engn, Shenzhen 518055, Peoples R China
[3] Harbin Inst Technol, Guangdong Prov Key Lab Aerosp Commun & Networking, Shenzhen 518055, Peoples R China
[4] Robot Soc, Shenzhen Inst Artificial Intelligence, Harbin Inst Technol, Shenzhen 518055, Peoples R China
[5] Huazhong Univ Sci & Technol, Hubei Engn Res Ctr Big Data Secur, Sch Cyber Sci & Engn, Hubei Key Lab Distributed Syst Secur, Wuhan, Peoples R China
来源
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING | 2023年 / 10卷 / 03期
基金
中国国家自然科学基金;
关键词
Games; Degradation; Costs; Behavioral sciences; Pricing; Servers; Quality of service; Game theory; mobile edge caching; network economics; peer content sharing; COMMUNICATION; INTERNET;
D O I
10.1109/TNSE.2022.3225021
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Mobile edge caching allows edge devices to cache popular contents and deliver them to end-users directly, and hence can effectively alleviate the increasingly heavy backbone loads and improve the quality-of-service of end-users. Peer content sharing enables edge devices to share the cached contents with each other, and can further increase the caching capability and efficiency. While lots of research efforts have been made to edge caching or content sharing, it remains largely open to devise a joint caching and sharing framework and study the complicated technical and economic interplay between both technologies. In this paper, we propose a joint framework for mobile edge caching and peer content sharing, and focus on studying the strategic behaviors and interactions of edge devices in the joint framework. Specifically, we model their interactions as a non-cooperative game, where each edge device (player) can choose to be an agent (who caches and shares contents with others) or a requester (who doesn't cache but requests contents from other devices) of each content. We characterize the game equilibrium under a generic usage-based pricing scheme (for content sharing) and analyze its existence and uniqueness systematically. We further design a best response based iterative learning algorithm for players to update their behaviors and reach the equilibrium in a self-enforcing manner. Moreover, we analyze the Price of Anarchy (PoA) of the game equilibrium to measure the system performance degradation due to the selfish strategic behaviors of game players, based on which we further design a pricing scheme (for content sharing) to reduce such performance degradation. Simulations show that our framework can reduce the total system cost by up to 60%, comparing with the benchmark pure caching system without peer content sharing.
引用
收藏
页码:1445 / 1461
页数:17
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