Information-Theoretic Caching: The Multi-User Case

被引:20
作者
Lim, Sung Hoon
Wang, Chien-Yi
Gastpar, Michael
机构
[1] Korea Institute of Ocean Science and Technology, Ansan
[2] MediaTek Inc., Hsinchu
[3] School of Computer and Communication Sciences, EPFL, Lausanne
基金
瑞士国家科学基金会; 新加坡国家研究基金会;
关键词
Coded caching; function computation; multi terminal source coding; source coding with side information; FUNDAMENTAL LIMITS;
D O I
10.1109/TIT.2017.2733527
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we consider a cache aided network in which each user is assumed to have individual caches, while upon users' requests, an update message is sent through a common link to all users. First, we formulate a general information theoretic setting that represents the database as a discrete memoryless source, and the users' requests as side information that is available everywhere except at the cache encoder. The decoders' objective is to recover a function of the source and the side information. By viewing cache aided networks in terms of a general distributed source coding problem and through information theoretic arguments, we present inner and outer bounds on the fundamental tradeoff of cache memory size and update rate. Then, we specialize our general inner and outer bounds to a specific model of content delivery networks: file selection networks, in which the database is a collection of independent equal-size files and each user requests one of the files independently. For file selection networks, we provide an outer bound and two inner bounds (for centralized and decentralized caching strategies). For the case when the user request information is uniformly distributed, we characterize the rate versus cache size tradeoff to within a multiplicative gap of 4. By further extending our arguments to the framework of Maddah-Ali and Niesen, we also establish a new outer bound and two new inner bounds in which it is shown to recover the centralized and decentralized strategies, previously established by Maddah-Ali and Niesen. Finally, in terms of rate versus cache size tradeoff, we improve the previous multiplicative gap of 72 to 4.7 for the average case with unitbrm requests.
引用
收藏
页码:7018 / 7037
页数:20
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