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: "lorawan in the wild measurements from the things network"
  Abstract: The Long-Range Wide-Area Network (LoRaWAN) specification was released in 2015, primarily to support the Internet-of-Things by facilitating wireless communication over long distances. Since 2015, the role-out and adoption of LoRaWAN has seen a steep growth. To the best of our knowledge, we are the first to have extensively measured, analyzed, and modeled the performance, features, and use cases of an operational LoRaWAN, namely The Things Network. Our measurement data, as presented in this paper, cover the early stages up to the production-level deployment of LoRaWAN. In particular, we analyze packet payloads, radio-signal quality, and spatio-temporal aspects, to model and estimate the performance of LoRaWAN. We also use our empirical findings in simulations to estimate the packet-loss.

Connected through hyperedge HE-1 (induced by source paper "lora in the field insights from networking the smart city hamburg with riot"):
  with members:
    - "long range communications in unlicensed bands the rising stars in the iot and smart city scenarios"

Connected through hyperedge HE-2 (induced by source paper "measurement characterization and modeling of lora technology in multi floor buildings"):
  with members:
    - "realistic indoor path loss modeling for regular wifi operations in india"
    - "in building wideband partition loss measurements at 2 5 and 60 ghz"

Connected through hyperedge HE-3 (induced by source paper "grant free radio access iot networks scalability analysis in coexistence scenarios"):
  with members:
    - "grant free radio access for short packet communications over 5g networks"
    - "on lorawan scalability empirical evaluation of susceptibility to inter network interference"
    - "low power wide area network analysis can lora scale"
    - "e 2 mac energy efficient medium access for massive m2m communications"
    - "understanding the limits of lorawan"
    - "2d time frequency interference modelling using stochastic geometry for performance evaluation in low power wide area networks"
    - "long range communications in unlicensed bands the rising stars in the iot and smart city scenarios"

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)