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: "software defined network controlled switching between millimeter wave and terahertz small cells"
  Abstract: Small cells are a cost-effective way to reliably expand network coverage and provide significantly increased capacity for end users. The ultra-high bandwidth available at millimeter (mmWave) and Terahertz (THz) frequencies can effectively realize short-range wireless access links in small cells enabling potential uses cases such as driver-less cars, data backhauling and ultra-high-definition infotainment services. This paper describes a new software defined network (SDN) framework for vehicles equipped with transceivers capable of dynamically switching between THz and mmWave bands. We present a novel SDN controlled admission policy that preferentially handoffs between the mmWave and THz small cells, accommodates asymmetric uplink/downlink traffic, performs error recovery and handles distinct link states that arise due to motion along practical vehicular paths. We then analytically derive the resulting capacity of such a small cell network by accounting for the channel characteristics unique to both these spectrum bands, relative distance and the contact times between a given transceiver pair. We then formulate the optimal procedure for scheduling multiple vehicles at a given infrastructure tower, with regards to practical road congestion scenarios. The search for the optimal schedule is shown to be a NP-hard problem. Hence, we design a computationally-feasible polynomial-time scheduling algorithm that runs at the SDN controller and compare its performance against the optimal procedure and random access. Additionally, we present a simulation-based case study for the use case of data center backhauling in Boston city to showcase the benefits of our approach.

Connected through hyperedge HE-1 (induced by source paper "risk based optimization of virtual reality over terahertz reconfigurable intelligent surfaces"):
  with members:
    - "on the reliability of wireless virtual reality at terahertz thz frequencies"
    - "a vision of 6g wireless systems applications trends technologies and open research problems"
    - "reconfigurable intelligent surfaces for energy efficiency in wireless communication"
    - "human in the loop wireless communications machine learning and brain aware resource management"
    - "urllc embb slicing to support vr multimodal perceptions over wireless cellular systems"
    - "virtual reality over wireless networks quality of service model and learning based resource management"
    - "rl 2 fast reinforcement learning via slow reinforcement learning"
    - "artificial neural networks based machine learning for wireless networks a tutorial"

Connected through hyperedge HE-2 (induced by source paper "mac protocols for terahertz communication a comprehensive survey"):
  with members:
    - "on the reliability of wireless virtual reality at terahertz thz frequencies"
    - "a tutorial on beam management for 3gpp nr at mmwave frequencies"
    - "on unified vehicular communications and radar sensing in millimeter wave and low terahertz bands"
    - "survey on terahertz nanocommunication and networking a top down perspective"
    - "end to end simulation of 5g mmwave networks"
    - "wireless terahertz system architectures for networks beyond 5g"
    - "terahertz technologies to deliver optical network quality of experience in wireless systems beyond 5g"
    - "slotted csma ca based energy efficient mac protocol design in nanonetworks"

Connected through hyperedge HE-3 (induced by source paper "on the reliability of wireless virtual reality at terahertz thz frequencies"):
  with members:
    - "a vision of 6g wireless systems applications trends technologies and open research problems"
    - "edge computing meets millimeter wave enabled vr paving the way to cutting the cord"
    - "urllc embb slicing to support vr multimodal perceptions over wireless cellular systems"
    - "virtual reality over wireless networks quality of service model and learning based resource management"

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)