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: "analysis of latency and mac layer performance for class a lorawan"
  Abstract: We propose analytical models that allow us to investigate the performance of long range wide area network (LoRaWAN) uplink in terms of latency, collision rate, and throughput under the constraints of the regulatory duty cycling, when assuming exponential inter-arrival times. Our models take into account sub-band selection and the case of sub-band combining. Our numerical evaluations consider specifically the European ISM band, but the analysis is applicable to any coherent band. Protocol simulations are used to validate the proposed models. We find that sub-band selection and combining have a large effect on the quality of service (QoS) experienced in an LoRaWAN cell for a given load. The proposed models allow for the optimization of resource allocation within a cell given a set of QoS requirements and a traffic model.

Connected through hyperedge HE-1 (induced by source paper "a thorough study of lorawan performance under different parameter settings"):
  with members:
    - "employing p csma on a lora network simulator"
    - "uncoordinated access schemes for the iot approaches regulations and performance"
    - "does bidirectional traffic do more harm than good in lorawan based lpwa networks"
    - "scalability analysis of large scale lorawan networks in ns 3"
    - "m2m massive access in lte rach performance evaluation in a smart city scenario"
    - "internet of things applications and challenges in technology and standardization"

Connected through hyperedge HE-2 (induced by source paper "a complete lorawan model for single gateway scenarios"):
  with members:
    - "a thorough study of lorawan performance under different parameter settings"
    - "does bidirectional traffic do more harm than good in lorawan based lpwa networks"
    - "scalability analysis of large scale lorawan networks in ns 3"
    - "low power wide area network analysis can lora scale"

Connected through hyperedge HE-3 (induced by source paper "analysis of lorawan uplink with multiple demodulating paths and capture effect"):
  with members:
    - "lora throughput analysis with imperfect spreading factor orthogonality"
    - "scalability analysis of a lora network under imperfect orthogonality"
    - "low power wide area network analysis can lora scale"

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)