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 "placing dynamic content in caches with small population"):
  Abstract: This paper addresses a fundamental limitation for the adoption of caching for wireless access networks due to small population sizes. This shortcoming is due to two main challenges: making timely estimates of varying content popularity and inferring popular content from small samples. We propose a framework which alleviates such limitations. To timely estimate varying popularity in a context of a single cache we propose an Age-Based Threshold (ABT) policy which caches all contents requested more times than a threshold N (τ), where τ is the content age. We show that ABT is asymptotically hit rate optimal in the many contents regime, which allows us to obtain the first characterization of the optimal performance of a caching system in a dynamic context. We then address small sample sizes focusing on L local caches and one global cache. On the one hand we show that the global cache learns L times faster by aggregating all requests from local caches, which improves hit rates. On the other hand, aggregation washes out local characteristics of correlated traffic which penalizes hit rate. This motivates coordination mechanisms which combine global learning of popularity scores in clusters and Least-Recently-Used (LRU) policy with prefetching.

Includes members:
  Member "wireless device to device caching networks basic principles and system performance":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "joint optimization of file placement and delivery in cache assisted wireless networks with limited lifetime and cache space")
  Member "catalog dynamics impact of content publishing and perishing on the performance of a lru cache":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "online convex optimization for caching networks")
  Member "modeling and predicting popularity dynamics via reinforced poisson processes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "deepcp deep learning driven cascade prediction based autonomous content placement in closed social network")
  Member "what will 5g be":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "5g network slicing using sdn and nfv a survey of taxonomy architectures and future challenges")
  Member "serving content with unknown demand the high dimensional regime":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "resource pooling in large scale content delivery systems")
  Member "exploring the memory bandwidth tradeoff in an information centric network":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "cache optimization models and algorithms")
  Member "asymptotic laws for joint content replication and delivery in wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "reinforcement learning based cooperative coded caching under dynamic popularities in ultra dense networks")
  Member "fundamental limits of caching":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "fundamental limits of wireless caching under mixed cacheable and uncacheable traffic")

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)