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Decentralized Coded Caching Attains Order-Optimal Memory-Rate Tradeoff
Abstract
Replicating or caching popular content in memories distributed across the network is a technique to reduce peak network loads. Conventionally, the main performance gain of this caching was thought to result from making part of the requested data available closer to end-users. Instead, we recently showed that a much more significant gain can be achieved by using caches to create coded-multicasting opportunities, even for users with different demands, through coding across data streams. These coded-multicasting opportunities are enabled by careful content overlap at the various caches in the network, created by a central coordinating server. In many scenarios, such a central coordinating server may not be available, raising the question if this multicasting gain can still be achieved in a more decentralized setting. In this paper, we propose an efficient caching scheme, in which the content placement is performed in a decentralized manner. In other words, no coordination is required for the content placement. Despite this lack of coordination, the proposed scheme is nevertheless able to create coded-multicasting opportunities and achieves a rate close to the optimal centralized scheme.
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Maddah-Ali, M. A., & Niesen, U. (2014) · IEEE Transactions on Information Theory · doi:10.1109/tit.2014.2306938 · Cited by 1,726
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Cited by
Speeding Up Distributed Machine Learning Using Codes
Lee, K., Lam, M., Pedarsani, R., Papailiopoulos, D., & Ramchandran, K. (2018) · IEEE Transactions on Information Theory · doi:10.1109/tit.2017.2736066 · Cited by 829
Base-Station Assisted Device-to-Device Communications for High-Throughput Wireless Video Networks
Golrezaei, N., Mansourifard, P., Molisch, A. F., & Dimakis, A. G. (2014) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2014.2316817 · Cited by 448
Li, L., Zhao, G., & Blum, R. S. (2018) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2018.2820021 · Cited by 282
Optimal and Scalable Caching for 5G Using Reinforcement Learning of Space-Time Popularities
Sadeghi, A., Sheikholeslami, F., & Giannakis, G. B. (2018) · IEEE Journal of Selected Topics in Signal Processing · doi:10.1109/jstsp.2017.2787979 · Cited by 257
Metadata
- Authors
- Maddah-Ali, M. A., & Niesen, U.
- Venue
- IEEE/ACM Transactions on Networking
- Published
- 2015-08
- Volume
- 23
- Issue
- 4
- Pages
- 1029-1040
- ISSN
- 1063-6692 (ISSN-L)
- 1558-2566
- OpenAlex
- W1990395546
- Cited by
- 626
- References
- 1
- FWCI
- 77.82
- Type
- journal article
- Language
- en
- Open access
- closed
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