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: "temporal correlation of interference in vehicular networks with shifted exponential time headways"
  Abstract: We consider a one-dimensional vehicular network where the time headway (time difference between successive vehicles as they pass a point on the roadway) follows the shifted-exponential distribution. We show that neglecting the impact of shift in the deployment model, which degenerates the distribution of vehicles to a Poisson Point Process, overestimates the temporal correlation of interference at the origin. The estimation error becomes large at high traffic conditions and small time-lags.

Connected through hyperedge HE-1 (induced by source paper "performance of a link in a field of vehicular interferers with hardcore headway distance"):
  with members:
    - "the meta distribution of the sir in linear motorway vanets"
    - "temporal correlation of interference and outage in mobile networks over one dimensional finite regions"
    - "an analytical framework for coverage in cellular networks leveraging vehicles"
    - "coverage analysis of a vehicular network modeled as cox process driven by poisson line process"
    - "temporal correlation of interference in bounded mobile ad hoc networks with blockage"
    - "asymptotic deployment gain a simple approach to characterize the sinr distribution in general cellular networks"
    - "statistical modeling and probabilistic analysis of cellular networks with determinantal point processes"
    - "effect of spatial interference correlation on the performance of maximum ratio combining"

Connected through hyperedge HE-2 (induced by source paper "scheduling and power control for v2v broadcast communications with co channel and adjacent channel interference"):
  with members:
    - "a measurement based shadow fading model for vehicle to vehicle network simulations"
    - "simulation and measurement based vehicle to vehicle channel characterization accuracy and constraint analysis"

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)