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: "nova qoe driven optimization of dash based video delivery in networks"
  Abstract: We consider the problem of optimizing video delivery for a network supporting video clients streaming stored video. Specifically, we consider the problem of jointly optimizing network resource allocation and video quality adaptation. Our objective is to fairly maximize video clients' Quality of Experience (QoE) realizing tradeoffs among the mean quality, temporal variability in quality, and fairness, incorporating user preferences on rebuffering and cost of video delivery. We present a simple asymptotically optimal online algorithm, NOVA, to solve the problem. NOVA is asynchronous, and using minimal communication, distributes the tasks of resource allocation to network controller, and quality adaptation to respective video clients. Video quality adaptation in NOVA is also optimal for standalone video clients, and is well suited for use with DASH framework. Further, we extend NOVA for use with more general QoE models, networks shared with other traffic loads and networks using fixed/legacy resource allocation.

Connected through hyperedge HE-1 (induced by source paper "qoe management of multimedia streaming services in future networks a tutorial and survey"):
  with members:
    - "5g network slicing using sdn and nfv a survey of taxonomy architectures and future challenges"
    - "a novel qoe aware sdn enabled nfv based management architecture for future multimedia applications on 5g systems"
    - "mptcp meets fec supporting latency sensitive applications over heterogeneous networks"
    - "network slicing for 5g with sdn nfv concepts architectures and challenges"
    - "nfv and sdn key technology enablers for 5g networks"
    - "network slicing to enable scalability and flexibility in 5g mobile networks"
    - "balancing the migration of virtual network functions with replications in data centers"
    - "5g icn delivering icn services over 5g using network slicing"

Connected through hyperedge HE-2 (induced by source paper "fresher content or smoother playback a brownian approximation framework for scheduling real time wireless video streams"):
  with members:
    - "analysis of buffer starvation with application to objective qoe optimization of streaming services"

Connected through hyperedge HE-3 (induced by source paper "fresher content or smoother playback a brownian approximation framework for real time video delivery in wireless networks"):
  with members:
    - "optimal scheduling for fair resource allocation in ad hoc networks with elastic and inelastic traffic"

Connected through hyperedge HE-4 (induced by source paper "streaming video qoe modeling and prediction a long short term memory approach"):
  with members:
    - "state space lstm models with particle mcmc inference"
    - "modeling continuous video qoe evolution a state space approach"
    - "show attend and tell neural image caption generation with visual attention"
    - "neural adaptive sequential monte carlo"
    - "long term recurrent convolutional networks for visual recognition and description"
    - "modeling the time varying subjective quality of http video streams with rate adaptations"
    - "sequence to sequence learning with neural networks"

Connected through hyperedge HE-5 (induced by source paper "performance bound analysis for crowdsourced mobile video streaming"):
  with members:
    - "providing long term participation incentive in participatory sensing"
    - "a game theoretic analysis of user behaviors in crowdsourced wireless community networks"
    - "probe and adapt rate adaptation for http video streaming at scale"

Connected through hyperedge HE-6 (induced by source paper "caching meets millimeter wave communications for enhanced mobility management in 5g networks"):
  with members:
    - "modeling and analyzing millimeter wave cellular systems"
    - "mobility management for heterogeneous networks leveraging millimeter wave for seamless handover"
    - "echo state networks for proactive caching in cloud based radio access networks with mobile users"
    - "caching in the sky proactive deployment of cache enabled unmanned aerial vehicles for optimized quality of experience"
    - "local multipath model parameters for generating 5g millimeter wave 3gpp like channel impulse response"
    - "asymptotic deployment gain a simple approach to characterize the sinr distribution in general cellular networks"
    - "tractable model for rate in self backhauled millimeter wave cellular networks"
    - "exploiting user mobility for wireless content delivery"

Connected through hyperedge HE-7 (induced by source paper "a survey on qoe oriented wireless resources scheduling"):
  with members:
    - "an overview on resource allocation techniques for multi user mimo systems"
    - "a control theoretic approach to adaptive video streaming in dense wireless networks"
    - "wiflix adaptive video streaming in massive mu mimo wireless networks"
    - "rate adaptation and admission control for video transmission with subjective quality constraints"

Connected through hyperedge HE-8 (induced by source paper "optimal network assisted multi user dash video streaming"):
  with members:
    - "joint optimization of qoe and fairness through network assisted adaptive mobile video streaming"
    - "adaptive video streaming for wireless networks with multiple users and helpers"
    - "probe and adapt rate adaptation for http video streaming at 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)