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: "chinese internet as level topology"
  Abstract: The first complete measurement of the Chinese Internet topology at the autonomous systems (AS) level based on traceroute data probed from servers of major ISPs in mainland China is presented. Both the Chinese Internet AS graph and the global Internet AS graph can be accurately reproduced by the positive-feedback preference model with the same parameters. This result suggests that the Chinese Internet preserves well the topological characteristics of the global Internet. This is the first demonstration of the Internet's topological fractality, or self-similarity, performed at the level of topology evolution modelling.

Connected through hyperedge HE-1 (induced by source paper "characterizing and avoiding routing detours through surveillance states"):
  with members:
    - "nation state routing censorship wiretapping and bgp"

Connected through hyperedge HE-2 (induced by source paper "phase changes in the evolution of the ipv4 and ipv6 as level internet topologies"):
  with members:
    - "on cost effective communication network designing"
    - "modeling the ipv6 internet as level topology"
    - "the internet as level topology three data sources and one definitive metric"
    - "understanding the evolution dynamics of internet topology"
    - "revealing the autonomous system taxonomy the machine learning approach"
    - "the rich club phenomenon in the internet topology"
    - "accurately modeling the internet topology"

Connected through hyperedge HE-3 (induced by source paper "evolution of the internet as level ecosystem"):
  with members:
    - "graph annotations in modeling complex network topologies"
    - "an integrated model of traffic geography and economy in the internet"
    - "as relationships inference and validation"
    - "the workshop on internet topology wit report"
    - "systematic topology analysis and generation using degree correlations"
    - "the internet as level topology three data sources and one definitive metric"
    - "understanding the evolution dynamics of internet topology"
    - "revealing the autonomous system taxonomy the machine learning approach"

Connected through hyperedge HE-4 (induced by source paper "review a critical look at power law modelling of the internet"):
  with members:
    - "beyond node degree evaluating as topology models"
    - "a model of internet topology using k shell decomposition"
    - "the workshop on internet topology wit report"
    - "systematic topology analysis and generation using degree correlations"
    - "the internet as level topology three data sources and one definitive metric"
    - "exploring networks with traceroute like probes theory and simulations"
    - "the rich club phenomenon in the internet topology"
    - "accurately modeling the internet topology"

Connected through hyperedge HE-5 (induced by source paper "enhancing network transmission capacity by efficiently allocating node capability"):
  with members:
    - "on cost effective communication network designing"
    - "a model of internet topology using k shell decomposition"
    - "structural bottlenecks for communication in networks"
    - "the internet as level topology three data sources and one definitive metric"
    - "understanding the evolution dynamics of internet topology"
    - "accurately modeling the internet topology"

Connected through hyperedge HE-6 (induced by source paper "beyond node degree evaluating as topology models"):
  with members:
    - "systematic topology analysis and generation using degree correlations"
    - "the internet as level topology three data sources and one definitive metric"

Connected through hyperedge HE-7 (induced by source paper "the workshop on internet topology wit report"):
  with members:
    - "what is the real size of a sampled network the case of the internet"
    - "systematic topology analysis and generation using degree correlations"
    - "the internet as level topology three data sources and one definitive metric"
    - "exploring networks with traceroute like probes theory and simulations"

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)