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: "on compact routing for the internet"
  Abstract: The Internet's routing system is facing stresses due to its poor fundamental scaling properties. Compact routing is a research field that studies fundamental limits of routing scalability and designs algorithms that try to meet these limits. In particular, compact routing research shows that shortest-path routing, forming a core of traditional routing algorithms, cannot guarantee routing table (RT) sizes that on all network topologies grow slower than linearly as functions of the network size. However, there are plenty of compact routing schemes that relax the shortest-path requirement and allow for improved, sublinear RT size scaling that is mathematically provable for all static network topologies. In particular, there exist compact routing schemes designed for grids, trees, and Internet-like topologies that offer RT sizes that scale logarithmically with the network size.   In this paper, we demonstrate that in view of recent results in compact routing research, such logarithmic scaling on Internet-like topologies is fundamentally impossible in the presence of topology dynamics or topology-independent (flat) addressing. We use analytic arguments to show that the number of routing control messages per topology change cannot scale better than linearly on Internet-like topologies. We also employ simulations to confirm that logarithmic RT size scaling gets broken by topology-independent addressing, a cornerstone of popular locator-identifier split proposals aiming at improving routing scaling in the presence of network topology dynamics or host mobility. These pessimistic findings lead us to the conclusion that a fundamental re-examination of assumptions behind routing models and abstractions is needed in order to find a routing architecture that would be able to scale "indefinitely.

Connected through hyperedge HE-1 (induced by source paper "greedy routing and the algorithmic small world phenomenom"):
  with members:
    - "average distance in a general class of scale free networks with underlying geometry"
    - "an experimental investigation of hyperbolic routing with a smart forwarding plane in ndn"
    - "network mapping by replaying hyperbolic growth"
    - "geometric inhomogeneous random graphs"
    - "on the diameter of hyperbolic random graphs"
    - "four degrees of separation"
    - "sustaining the internet with hyperbolic mapping"
    - "networks become navigable as nodes move and forget"

Connected through hyperedge HE-2 (induced by source paper "scalable routing easy as pie a practical isometric embedding protocol technical report"):
  with members:
    - "sustaining the internet with hyperbolic mapping"
    - "the internet as level topology three data sources and one definitive metric"
    - "dimes let the internet measure itself"

Connected through hyperedge HE-3 (induced by source paper "on the hyperbolicity of small world and tree like random graphs"):
  with members:
    - "euclidean versus hyperbolic congestion in idealized versus experimental networks"

Connected through hyperedge HE-4 (induced by source paper "graph annotations in modeling complex network topologies"):
  with members:
    - "as relationships inference and validation"
    - "systematic topology analysis and generation using degree correlations"
    - "the internet as level topology three data sources and one definitive metric"
    - "revealing the autonomous system taxonomy the machine learning approach"
    - "exploring networks with traceroute like probes theory and simulations"
    - "inferring as relationships dead end or lively beginning"

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)