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: "optimization of quality of experience through file duplication in video sharing servers"
  Abstract: Consumers of short videos on Internet can have a bad Quality of Experience QoE due to the long distance between the consumers and the servers that hosting the videos. We propose an optimization of the file allocation in telecommunication operators content sharing servers to improve the QoE through files duplication, thus bringing the files closer to the consumers. This optimization allows the network operator to set the level of QoE and to have control over the users access cost by setting a number of parameters. Two optimization methods are given and are followed by a comparison of their efficiency. Also, the hosting costs versus the gain of optimization are analytically discussed.

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"
    - "flow level qoe of video streaming in wireless networks"
    - "caching eliminates the wireless bottleneck in video aware wireless networks"

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)