Fundamental Limits of Caching

• Published in: IEEE transactions on information theory Vol. 60; no. 5; pp. 2856 - 2867
• Main Authors: Maddah-Ali, Mohammad Ali, Niesen, Urs
• Format: Journal Article
• Language: English
• Published: New York IEEE 01-05-2014; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Aggregates; Cache memory; Caching; Codes; Constants; End users; Gain; Information theory; Multicast communication; Networks; Optimization; Prefetching; Radio frequency; Reproduction; Servers; Upper bound; content distribution; coded caching; Caching; prefetching
• ISSN: 0018-9448; 1557-9654
• DOI: 10.1109/TIT.2014.2306938

Caching is a technique to reduce peak traffic rates by prefetching popular content into memories at the end users. Conventionally, these memories are used to deliver requested content in part from a locally cached copy rather than through the network. The gain offered by this approach, which we term local caching gain, depends on the local cache size (i.e., the memory available at each individual user). In this paper, we introduce and exploit a second, global, caching gain not utilized by conventional caching schemes. This gain depends on the aggregate global cache size (i.e., the cumulative memory available at all users), even though there is no cooperation among the users. To evaluate and isolate these two gains, we introduce an information-theoretic formulation of the caching problem focusing on its basic structure. For this setting, we propose a novel coded caching scheme that exploits both local and global caching gains, leading to a multiplicative improvement in the peak rate compared with previously known schemes. In particular, the improvement can be on the order of the number of users in the network. In addition, we argue that the performance of the proposed scheme is within a constant factor of the information-theoretic optimum for all values of the problem parameters.