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 "q caching an integrated reinforcement learning approach for caching and routing in information centric networks"):
  Abstract: Content delivery, such as video streaming, is one of the most prevalent Internet applications. Although very popular, the continuous growth of such applications poses novel performance and scalability challenges. Information-centric networks put content at the center, and propose novel solutions to such challenges but also pose new questions on the interface between caching and routing. In this paper, building on top of Q-routing we propose a caching strategy, namely Q-caching, which leverages information that is already collected by the routing algorithm. Q-caching promotes content diversity in the network, reducing the load at custodians and average download times for clients. In stylized topologies, we show that the gains of Q-caching against state-of-the-art algorithms are significant. We then consider the RNP topology, and show that Q-caching performance is more flexible while competitive when compared against existing algorithms.

Includes members:
  Member "a utility optimization approach to network cache design":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "online convex optimization for caching networks")
  Member "enabling correct interest forwarding and retransmissions in a content centric network":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "adn an information centric networking architecture for the internet of things")
  Member "enabling information centric networks through opportunistic search routing and caching":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "flexible content placement in cache networks using reinforced counters")
  Member "a general tractable and accurate model for a cascade of caches":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "flexible content placement in cache networks using reinforced counters")

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)