期刊
IEEE TRANSACTIONS ON COMMUNICATIONS
卷 69, 期 4, 页码 2138-2147出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCOMM.2020.3047621
关键词
Libraries; Base stations; Indexes; Delays; Minimization; Load modeling; Distributed databases; Caching; content delivery networks; erasure correcting codes; TTL
资金
- Swedish Research Council [201604253]
- National Center for Scientific Research in France [CNRS-PICS-2016-DISCO]
The study focuses on distributed and dynamic caching of coded content at small base stations (SBSs) in an area served by a macro base station (MBS), using time-to-live (TTL) cache eviction policy to minimize overall network load, especially when request arrivals are bursty. The problem can be analyzed as a convex optimization problem for a specific single cache, showing that static caching is optimal under a Poisson request process.
We consider distributed and dynamic caching of coded content at small base stations (SBSs) in an area served by a macro base station (MBS). Specifically, content is encoded using a maximum distance separable code and cached according to a time-to-live (TTL) cache eviction policy, which allows coded packets to be removed from the caches at periodic times. Mobile users requesting a particular content download coded packets from SBSs within communication range. If additional packets are required to decode the file, these are downloaded from the MBS. We formulate an optimization problem that is efficiently solved numerically, providing TTL caching policies minimizing the overall network load. We demonstrate that distributed coded caching using TTL caching policies can offer significant reductions in terms of network load when request arrivals are bursty. We show how the distributed coded caching problem utilizing TTL caching policies can be analyzed as a specific single cache, convex optimization problem. Our problem encompasses static caching and the single cache as special cases. We prove that, interestingly, static caching is optimal under a Poisson request process, and that for a single cache the optimization problem has a surprisingly simple solution.
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