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: "lwip and wi fi boost link management"
  Abstract: 3GPP LWIP Release 13 technology and its prestandard version Wi-Fi Boost have recently emerged as an efficient LTE and Wi-Fi integration at the IP layer, allowing uplink on LTE and downlink on Wi-Fi. This solves all the contention problems of Wi-Fi and allows an optimum usage of the unlicensed band for downlink. In this paper, we present a new feature of Wi-Fi Boost, its radio link management, which allows to steer the downlink traffic between both LTE and Wi-Fi upon congestion detection in an intelligent manner. This customised congestion detection algorithm is based on IP probing, and can work with any Wi-Fi access point. Simulation results in a typical enterprise scenario show that LWIP R13 and Wi-Fi Boost can enhance network performance up to 5x and 6x over LTE-only, and 4x and 5x over Wi-Fi only networks, respectively, and that the the proposed radio link management can further improve Wi-Fi Boost performance over LWIP R13 up to 19 %. Based on the promising results, this paper suggests to enhance LWIP R13 user feedback in future LTE releases.

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)