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: "a simulation environment and preliminary evaluation for automotive can ethernet avb networks"
  Abstract: Ethernet is being considered as the backbone network protocol for next-generation automotive control networks. In such networks, Controller Area Network (CAN) messages related to automotive control can be sent from a CAN network to other sub-networks via the backbone Ethernet bus and, if the CAN messages have real-time constraints, these have to be guaranteed. This paper presents a simulation environment for CAN--Ethernet Audio Video Bridging (AVB) mixed networks based on OMNeT++. We use Ethernet AVB, which can guarantee network bandwidth, to improve the real-time property of CAN messages through the backbone Ethernet bus. To simulate the networks, we also developed a CAN--Ethernet AVB gateway (GW) model. To verify the efficacy of our model, we measured the latency of CAN messages sent from a CAN bus to an Ethernet AVB node via the backbone Ethernet AVB bus in both bandwidth-guaranteed and best-effort queue scenarios. The results indicate that the latency of Ethernet AVB frames containing CAN messages is minimized and limited by the bandwidth-guaranteed mechanism of Ethernet AVB.

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)