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: "network connectivity stochastic vs deterministic wireless channels"
  Abstract: We study the effect of stochastic wireless channel models on the connectivity of ad hoc networks. Unlike in the deterministic geometric disk model where nodes connect if they are within a certain distance from each other, stochastic models attempt to capture small-scale fading effects due to shadowing and multipath received signals. Through analysis of local and global network observables, we present conclusive evidence suggesting that network behaviour is highly dependent upon whether a stochastic or deterministic connection model is employed. Specifically we show that the network mean degree is lower (higher) for stochastic wireless channels than for deterministic ones, if the path loss exponent is greater (lesser) than the spatial dimension. Similarly, the probability of forming isolated pairs of nodes in an otherwise dense random network is much less for stochastic wireless channels than for deterministic ones. The latter realisation explains why the upper bound of $k$-connectivity is tighter for stochastic wireless channels. We obtain closed form analytic results and compare to extensive numerical simulations.

Connected through hyperedge HE-1 (induced by source paper "fading improves connectivity in vehicular ad hoc networks"):
  with members:
    - "multihop cluster based ieee 802 11p and lte hybrid architecture for vanet safety message dissemination"
    - "empirical study of traffic velocity distribution and its effect on vanets connectivity"

Connected through hyperedge HE-2 (induced by source paper "spatial networks with wireless applications"):
  with members:
    - "boundaries as an enhancement technique for physical layer security"
    - "on the capacity of fractal wireless networks with direct social interactions"
    - "correlated interference from uncorrelated users in bounded ad hoc networks with blockage"
    - "coverage analysis of a vehicular network modeled as cox process driven by poisson line process"
    - "on the capacity of wireless networks with fractal and hierarchical social communications"
    - "boundaries can enhance physical layer security at high data rates"
    - "temporal correlation of interference in bounded mobile ad hoc networks with blockage"
    - "interference functionals in poisson networks"

Connected through hyperedge HE-3 (induced by source paper "distributed power allocation and channel access probability assignment for cognitive radio"):
  with members:
    - "network connectivity in non convex domains with reflections"

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)