human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "adapting caching to audience retention rate which video chunk to store"):
  Abstract: Rarely do users watch online contents entirely. We study how to take this into account to improve the performance of cache systems for video-on-demand and video-sharing platforms in terms of traffic reduction on the core network. We exploit the notion of "Audience retention rate", introduced by mainstream online content platforms and measuring the popularity of different parts of the same video content. We first characterize the performance limits of a cache able to store parts of videos, when the popularity and the audience retention rate of each video are available to the cache manager. We then relax the assumption of known popularity and we propose a LRU (Least Recently Used) cache replacement policy that operates on the first chunks of each video. We characterize its performance by extending the well-known Che's approximation to this case. We prove that, by refining the chunk granularity, the chunk-LRU policy increases its performance. It is shown numerically that even for a small number of chunks (N=20), the gains of chunk-LRU are still significant in comparison to standard LRU policy that caches entire files, and they are almost optimal.

Includes members:
  Member "exploring the memory bandwidth tradeoff in an information centric network":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "cache optimization models and algorithms")
  Member "a versatile and accurate approximation for lru cache performance":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "online convex optimization for caching networks")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.NI(Networking and Internet Architecture)