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: "hierarchical routing over dynamic wireless networks"
  Abstract: Wireless network topologies change over time and maintaining routes requires frequent updates. Updates are costly in terms of consuming throughput available for data transmission, which is precious in wireless networks. In this paper, we ask whether there exist low-overhead schemes that produce low-stretch routes. This is studied by using the underlying geometric properties of the connectivity graph in wireless networks.

Connected through hyperedge HE-1 (induced by source paper "comparison based learning from weak oracles"):
  with members:
    - "active ranking from pairwise comparisons and when parametric assumptions don t help"
    - "learning combinatorial functions from pairwise comparisons"
    - "leveraging transitive relations for crowdsourced joins"
    - "crowder crowdsourcing entity resolution"
    - "comparison based learning with rank nets"
    - "adaptively learning the crowd kernel"
    - "adaptive submodularity theory and applications in active learning and stochastic optimization"
    - "approximate nearest neighbor search for low dimensional queries"

Connected through hyperedge HE-2 (induced by source paper "multiscale gossip for efficient decentralized averaging in wireless packet networks"):
  with members:
    - "location aided fast distributed consensus in wireless networks"
    - "gossip algorithms for distributed signal processing"
    - "optimization and analysis of distributed averaging with short node memory"
    - "distributed averaging via lifted markov chains"
    - "polynomial filtering for fast convergence in distributed consensus"
    - "geographic gossip efficient averaging for sensor networks"
    - "order optimal consensus through randomized path averaging"
    - "hierarchical cooperation achieves optimal capacity scaling in ad hoc networks"

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)