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: "qos aware routing in wireless networks using aerial vehicles"
  Abstract: The next generation wireless networks need efficient mechanisms for data dissemination that should support users with better Quality of Service (QoS). Nevertheless, the existing solutions are unable to handle this demand and require either network redeployment or replanning. Moreover, this upsurges the overall operational cost and complexity of the network. This problem can be addressed by deploying Unmanned Aerial Vehicles (UAVs), which can act as on-demand relays in next generation wireless networks. In this work, a novel strategy comprising a series of algorithms based on neural networks is devised, which resolves the issues related to data dissemination, QoS, capacity, and coverage. When compared with the existing methods, the proposed approach demonstrates better outcomes for various parameters, namely, throughput, message disseminations, service dissemination rate, UAV allocation time, route acquisition delay, link utilization and signal to noise ratio for end users. The experimental results exhibit the fact that the proposed approach utilizes 39.6%, 41.6%, 43.5%, 44.4%, and 46.9% lesser iterations than the EEDD, A-Star, OCD, GPCR, and GyTAR, respectively. Therefore, it is evident that the proposed approach surpasses the existing methods by means of superior performance and augmented efficiency.

Connected through hyperedge HE-1 (induced by source paper "an optimal security management framework for backhaul aware 5g vehicle to everything v2x"):
  with members:
    - "a security credential management system for v2x communications"
    - "security management for backhaul aware 5g v2x"
    - "optimized certificate revocation list distribution for secure v2x communications"

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)