human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "effect of spatial and temporal traffic statistics on the performance of wireless networks"):
  Abstract: The traffic in wireless networks has become diverse and fluctuating both spatially and temporally due to the emergence of new wireless applications and the complexity of scenarios. The purpose of this paper is to explore the impact of the wireless traffic, which fluctuates violently both spatially and temporally, on the performance of the wireless networks. Specially, we propose to combine the tools from stochastic geometry and queueing theory to model the spatial and temporal fluctuation of traffic, which to our best knowledge has seldom been evaluated analytically. We derive the spatial and temporal statistics, the total arrival rate, the stability of queues and the delay of users by considering two different spatial properties of traffic, i.e., the uniformly and non-uniformly distributed cases. The numerical results indicate that although the fluctuations of traffic when the users are clustered, reflected by the variance of total arrival rate, is much fiercer than that when the users are uniformly distributed, the stability performance is much better. Our work provides a useful reference for the design of wireless networks when the complex spatio-temporal fluctuation of the traffic is considered.

Includes members:
  Member "tradeoff between delay and physical layer security in wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "spatio temporal modeling for massive and sporadic access")
  Member "the meta distribution of the sir for cellular networks with power control":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a spatiotemporal framework for information freshness in iot uplink networks")
  Member "stable throughput and delay analysis of a random access network with queue aware transmission":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "performance analysis of a cooperative wireless network with adaptive relays")
  Member "random access analysis for massive iot networks under a new spatio temporal model a stochastic geometry approach":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "spatio temporal modeling for massive and sporadic access")
  Member "spatiotemporal stochastic modeling of iot enabled cellular networks scalability and stability analysis":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "optimizing information freshness in wireless networks a stochastic geometry approach")
  Member "poisson cluster process based analysis of hetnets with correlated user and base station locations":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "joint energy and sinr coverage in spatially clustered rf powered iot network")
  Member "heterogeneous cellular networks with spatio temporal traffic delay analysis and scheduling":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "optimizing information freshness in wireless networks a stochastic geometry approach")
  Member "the learning and prediction of application level traffic data in cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "predictive deployment of uav base stations in wireless networks machine learning meets contract theory")

Question: Please tell me which class the source paper 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)