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: "a geographic directed preferential internet topology model"
  Abstract: The goal of this work is to model the peering arrangements between Autonomous Systems (ASes). Most existing models of the AS-graph assume an undirected graph. However, peering arrangements are mostly asymmetric Customer-Provider arrangements, which are better modeled as directed edges. Furthermore, it is well known that the AS-graph, and in particular its clustering structure, is influenced by geography. #R##N#We introduce a new model that describes the AS-graph as a directed graph, with an edge going from the customer to the provider, but also models symmetric peer-to-peer arrangements, and takes geography into account. We are able to mathematically analyze its power-law exponent and number of leaves. Beyond the analysis we have implemented our model as a synthetic network generator we call GdTang. Experimentation with GdTang shows that the networks it produces are more realistic than those generated by other network generators, in terms of its power-law exponent, fractions of customer-provider and symmetric peering arrangements, and the size of its dense core. We believe that our model is the first to manifest realistic regional dense cores that have a clear geographic flavor. Our synthetic networks also exhibit path inflation effects that are similar to those observed in the real AS graph.

Connected through hyperedge HE-1 (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"
    - "chinese internet as level topology"
    - "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"

Connected through hyperedge HE-2 (induced by source paper "an integrated model of traffic geography and economy in the internet"):
  with members:
    - "radial structure of the internet"

Connected through hyperedge HE-3 (induced by source paper "bounding the bias of tree like sampling in ip topologies"):
  with members:
    - "what is the real size of a sampled network the case of the internet"
    - "exploring networks with traceroute like probes theory and simulations"
    - "dimes let the internet measure itself"

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)