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: "bounding queue delay in cellular networks to support ultra low latency applications"
  Abstract: Most of the current active queue management (AQM) designs have major issues including severe hardship of being tuned for highly fluctuated cellular access link bandwidths. Consequently, most of the cellular network providers either give up using AQMs or use conservative offline configurations for them. However, these choices will significantly impact the performance of the emerging interactive and highly delay sensitive applications such as virtual reality and vehicle-to-vehicle communications. #R##N#Therefore, in this paper, we investigate the problems of existing AQM schemes and show that they are not suitable options to support ultra-low latency applications in a highly dynamic network such as current and future cellular networks. Moreover, we believe that achieving good performance does not necessarily come from complex drop rate calculation algorithms or complicated AQM techniques. Consequently, we propose BoDe an extremely simple and deployment friendly AQM scheme to bound the queuing delay of served packets and support ultra-low latency applications. #R##N#We have evaluated BoDe in extensive trace-based evaluations using cellular traces from 3 different service providers in the US and compared its performance with state-of-the-art AQM designs including CoDel and PIE under a variety of streaming applications, video conferencing applications, and various recently proposed TCP protocols. Results show that despite BoDe's simple design, it outperforms other schemes and achieves significantly lower queuing delay in all tested scenarios.

Connected through hyperedge HE-1 (induced by source paper "sharpedge an asynchronous and core agnostic solution to guarantee bounded delays"):
  with members:
    - "make tcp great again in cellular networks a deep reinforcement learning approach"
    - "toward optimal performance with network assisted tcp at mobile edge"
    - "hyline a simple and practical flow scheduling for commodity datacenters"
    - "cellular controlled delay tcp c2tcp"
    - "c2tcp a flexible cellular tcp to meet stringent delay requirements"
    - "finishing flows quickly with preemptive scheduling"

Connected through hyperedge HE-2 (induced by source paper "make tcp great again in cellular networks a deep reinforcement learning approach"):
  with members:
    - "on the generalization gap in reparameterizable reinforcement learning"
    - "toward optimal performance with network assisted tcp at mobile edge"
    - "learning and generalization in overparameterized neural networks going beyond two layers"
    - "learning to adapt in dynamic real world environments through meta reinforcement learning"
    - "quantifying generalization in reinforcement learning"
    - "cellular controlled delay tcp c2tcp"
    - "c2tcp a flexible cellular tcp to meet stringent delay requirements"
    - "successor features for transfer in reinforcement learning"

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)