Distributed Caching Algorithms for Content Distribution Networks

By S. Borst, Varun Gupta, Anwar Elwalid. 2010 Proceedings IEEE INFOCOM, 2010

605 citations recorded by the source corpus.

Subfields: Computer Networks and Communications

View Paper: https://www.semanticscholar.org/paper/7b8d5f8518e9aff9f98e4146179f30f1ad305cd2

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Citations in the corpus

FemtoCaching: Wireless video content delivery through distributed caching helpers (2011, background): “ser connects to it. Different procedures for caching have been analyzed with the aim to support mobility. For more references, we refer the reader to references in [17]. In another line of work, [18] [19], cache placement problems have been considered for the content distribution networks which form”
Coded caching with nonuniform demands (2013, background): “n the placement phase and the reconstruction constraint in the delivery phase. Designing and analyzing caching systems for such (and more complicated) networks has a long history, see for example [2]–[7]. The impact of speciﬁc ﬁle popularit ies p 1,p 2,··· ,pN (such as Zipf or other heavy-tail distr”
FemtoCaching: Wireless Content Delivery Through Distributed Caching Helpers (2013, background): “In another line of work, [25], [26], cache placement problems have been considered for the content distribution networks which form a distributed caching infrastructure on the wired network.”
A Survey on End-Edge-Cloud Orchestrated Network Computing Paradigms (2019, positive): “To transmit video contents, the authors of Reference [23] develop a lightweight algorithm to achieve both the maximum of traffic volume served from cache and the minimum of the band-width cost for the cooperative cache management network.”
A Survey on Mobile Edge Networks: Convergence of Computing, Caching and Communications (2017, methodology): “The literature [95] reviews in detail the conventional caching policies and forwarding mechanism in information centric networks. we will present a taxonomy of the caching policies in wireless mobile networks in the following, which is summarized in Table VI. 1) Conventional Caching Policies: Conten”
Learning-based optimization of cache content in a small cell base station (2014, background): “The cache cluster in [6] is further studied in [7] for the case of equal size ﬁles and when leaf-cache nodes are not inter-connected, and a polynomial complexity optimal algorithm is given for the case of two leaf-cache nodes.”
Cache-enabled small cell networks: modeling and tradeoffs (2014, methodology): “During the emergence of CDNs, many caching algorithms such as in [14] have appeared.”
Fundamental Limits of Caching (2012, background): “As pointed out above, the gain from traditional uncoded caching approaches derives from making content available locally: if a user requests some content that is stored in its cache, this request can be served from its local memory.”
Caching in information centric networking: A survey (2013, background): “…b, Tao Lin b a School of Computer Science and Technology, Nanjing Normal University, Nanjing, China b High Performance Network Lab, Chinese Academy of Sciences, Beijing, China c Provincial Key Laboratory for Computer Information Processing Technology, Soochow University, Suzhou, China a r t i c l…”
Decentralized coded caching attains order-optimal memory-rate tradeoff (2013, background): “Extensive research has been done on this conventional caching approach, mainly on how to exploit differing file popularities to maximize the caching gain [1]–[7].”
The Exact Rate-Memory Tradeoff for Caching With Uncoded Prefetching (2016, background): “the chance that the requested content can be delivered locally [2]–[9].”