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: "flow level qoe of video streaming in wireless networks"
  Abstract: The Quality of Experience (QoE) of streaming service is often degraded by frequent playback interruptions. To mitigate the interruptions, the media player prefetches streaming contents before starting playback, at a cost of delay. We study the QoE of streaming from the perspective of flow dynamics. First, a framework is developed for QoE when streaming users join the network randomly and leave after downloading completion. We compute the distribution of prefetching delay using partial differential equations (PDEs), and the probability generating function of playout buffer starvations using ordinary differential equations (ODEs) for CBR streaming. Second, we extend our framework to characterize the throughput variation caused by opportunistic scheduling at the base station, and the playback variation of VBR streaming. Our study reveals that the flow dynamics is the fundamental reason of playback starvation. The QoE of streaming service is dominated by the first moments such as the average throughput of opportunistic scheduling and the mean playback rate. While the variances of throughput and playback rate have very limited impact on starvation behavior.

Connected through hyperedge HE-1 (induced by source paper "quality of experience for streaming services measurements challenges and insights"):
  with members:
    - "thirty years of machine learning the road to pareto optimal next generation wireless networks"
    - "learning to predict streaming video qoe distortions rebuffering and memory"
    - "modeling qoe of video streaming in wireless networks with large scale measurement of user behavior"
    - "optimization of quality of experience through file duplication in video sharing servers"
    - "caching eliminates the wireless bottleneck in video aware wireless networks"

Connected through hyperedge HE-2 (induced by source paper "outage performance of two hop ofdm systems with spatially random decode and forward relays"):
  with members:
    - "secrecy outage analysis for downlink transmissions in the presence of randomly located eavesdroppers"
    - "modeling heterogeneous network interference using poisson point processes"

Connected through hyperedge HE-3 (induced by source paper "computing quality of experience of video streaming in network with long range dependent traffic"):
  with members:
    - "adaptive video streaming for wireless networks with multiple users and helpers"
    - "analysis of buffer starvation with application to objective qoe optimization of streaming services"

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)