human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "enabling information centric networks through opportunistic search routing and caching"
  Abstract: Content dissemination networks are pervasive in todays Internet. Examples of content dissemination networks include peer-to-peer networks (P2P), content distribution networks (CDN) and information centric networks (ICN). In this paper, we propose a new system design for information centric networks which leverages opportunistic searching, routing and caching. Our system design is based on an hierarchical tiered structure. Random walks are used to find content inside each tier, and gateways across tiers are used to direct requests towards servers placed in the top tier, which are accessed in case content replicas are not found in lower tiers. Then, we propose a model to analyze the system in consideration. The model yields metrics such as mean time to find a content and the load experienced by custodians as a function of the network topology. Using the model, we identify trade-offs between these two metrics, and numerically show how to find the optimal time to live of the random walks.

Connected through hyperedge HE-1 (induced by source paper "q caching an integrated reinforcement learning approach for caching and routing in information centric networks"):
  with members:
    - "a utility optimization approach to network cache design"
    - "enabling correct interest forwarding and retransmissions in a content centric network"
    - "a general tractable and accurate model for a cascade of caches"

Connected through hyperedge HE-2 (induced by source paper "flexible content placement in cache networks using reinforced counters"):
  with members:
    - "exact analysis of ttl cache networks the case of caching policies driven by stopping times"
    - "a general tractable and accurate model for a cascade of caches"

Connected through hyperedge HE-3 (induced by source paper "on the optimization of bittorrent like protocols for interactive on demand streaming systems"):
  with members:
    - "on the scalability of p2p swarming systems"
    - "on client interactive behaviour to design peer selection policies for bittorrent like protocols"
    - "heterogeneous download times in a homogeneous bittorrent swarm"
    - "stability of a peer to peer communication system"
    - "rarest first and choke algorithms are enough"

Question: Please tell me which class the center node 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)