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: "performance analysis of dynamic channel bonding in spatially distributed high density wlans"
  Abstract: In this paper we discuss the effects on throughput and fairness of dynamic channel bonding (DCB) in spatially distributed high density (HD) wireless local area networks (WLANs). First, we present an analytical framework based on continuous time Markov networks (CTMNs) for depicting the phenomena given when applying different DCB policies in spatially distributed scenarios, where nodes are not required to be within the carrier sense of each other. Then, we assess the performance of DCB in HD IEEE 802.11ax WLANs by means of simulations. Regarding spatial distribution, we show that there may be critical interrelations among nodes - even if they are located outside the carrier sense range of each other - in a chain reaction manner. Results also show that, while always selecting the widest available channel normally maximizes the individual long-term throughput, it often generates unfair scenarios where other WLANs starve. Moreover, we show that there are scenarios where DCB with stochastic channel width selection improves the latter approach both in terms of individual throughput and fairness. It follows that there is not a unique DCB policy that is optimal for every case. Instead, smarter bandwidth adaptation is required in the challenging scenarios of next-generation WLANs.

Connected through hyperedge HE-1 (induced by source paper "potential and pitfalls of multi armed bandits for decentralized spatial reuse in wlans"):
  with members:
    - "to overlap or not to overlap enabling channel bonding in high density wlans"
    - "dynamic channel bonding in spatially distributed high density wlans"
    - "implications of decentralized q learning resource allocation in wireless networks"
    - "ieee 802 11ax high efficiency wlans"
    - "multi player bandits a musical chairs approach"
    - "joint channel selection and power control in infrastructureless wireless networks a multiplayer multiarmed bandit framework"
    - "channel selection for network assisted d2d communication via no regret bandit learning with calibrated forecasting"
    - "further optimal regret bounds for thompson sampling"

Connected through hyperedge HE-2 (induced by source paper "ap initiated multi user transmissions in ieee 802 11ax wlans"):
  with members:
    - "a high efficiency mac protocol for wlans providing fairness in dense scenarios"
    - "ieee 802 11ax high efficiency wlans"
    - "collision free operation in high density wlan deployments"
    - "on the interactions between multiple overlapping wlans using channel bonding"
    - "mu mimo mac protocols for wireless local area networks a survey"
    - "resource management for ofdma based next generation 802 11 wlans"
    - "analysis of dynamic channel bonding in dense networks of wlans"

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)