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: "scalable bgp prefix selection for effective inter domain traffic engineering"
  Abstract: Inter-domain Traffic Engineering for multi-homed networks faces a scalability challenge, as the size of BGP routing table continue to grow. In this context, the choice of the best path must be made potentially for each destination prefix, requiring all available paths to be characterised (e.g., through measurements) and compared with each other. Fortunately, it is well-known that a few number of prefixes carry the larger part of the traffic. As a natural consequence, to engineer large volume of traffic only few prefixes need to be managed. Yet, traffic characteristics of a given prefix can greatly vary over time, and little is known on the dynamism of traffic at this aggregation level, including predicting the set of the most significant prefixes in the near future. %based on past observations. Sophisticated prediction methods won't scale in such context. In this paper, we study the relationship between prefix volume, stability, and predictability, based on recent traffic traces from nine different networks. Three simple and resource-efficient methods to select the prefixes associated with the most important foreseeable traffic volume are then proposed. Such proposed methods allow to select sets of prefixes with both excellent representativeness (volume coverage) and stability in time, for which the best routes are identified. The analysis carried out confirm the potential benefits of a route decision engine.

Connected through hyperedge HE-1 (induced by source paper "one to one matching of rtt and path changes"):
  with members:
    - "traixroute detecting ixps in traceroute paths"
    - "evaluating real time anomaly detection algorithms the numenta anomaly benchmark"

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)