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 methodology for studying 802 11p vanet broadcasting performance with practical vehicle distribution"
  Abstract: In a vehicular ad hoc network (VANET), the performance of the communication protocol is heavily influenced by the vehicular density dynamics. However, most of the previous works on VANET performance modeling paid little attention to vehicle distribution or simply assumed homogeneous car distribution. It is obvious that vehicles are distributed nonhomogeneously along a road segment due to traffic signals and speed limits at different portions of the road, as well as vehicle interactions that are significant on busy streets. In light of the inadequacy, in this paper, we present an original methodology to study the broadcasting performance of 802.11p VANETs with practical vehicle distribution in urban environments. First, we adopt the empirically verified stochastic traffic models, which incorporate the effect of urban settings (such as traffic lights and vehicle interactions) on car distribution and generate practical vehicular density profiles. Corresponding 802.11p protocol and performance models are then developed. When coupled with the traffic models, they can predict broadcasting efficiency, delay, and throughput performances of 802.11p VANETs based on the knowledge of car density at each location on the road. Extensive simulation is conducted to verify the accuracy of the developed mathematical models with the consideration of vehicle interaction. In general, our results demonstrate the applicability of the proposed methodology on modeling protocol performance in practical signalized road networks and shed insights into the design and development of future communication protocols and networking functions for VANETs.

Connected through hyperedge HE-1 (induced by source paper "cooperative adaptive cruise control for connected autonomous vehicles by factoring communication related constraints"):
  with members:
    - "youtube av 50k an annotated corpus for comments in autonomous vehicles"
    - "cooperative adaptive cruise control for a platoon of connected and autonomous vehicles considering dynamic information flow topology"

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)