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: "virtualized control over fog interplay between reliability and latency"
  Abstract: This paper introduces an analytical framework to investigate optimal design choices for the placement of virtual controllers along the cloud-to-things continuum. The main application scenarios include low-latency cyber-physical systems in which real-time control actions are required in response to the changes in states of an IoT node. In such cases, deploying controller software on a cloud server is often not tolerable due to delay from the network edge to the cloud. Hence, it is desirable to trade reliability with latency by moving controller logic closer to the network edge. Modeling the IoT node as a dynamical system that evolves linearly in time with quadratic penalty for state deviations, recursive expressions for the optimum control policy and the resulting minimum cost value are obtained by taking virtual fog controller reliability and response time latency into account. Our results indicate that latency is more critical than reliability in provisoning virtualized control services over fog endpoints, as it determines the swiftness of the fog control system as well as the timeliness of state measurements. Based on a realistic drone trajectory tracking model, an extensive simulation study is also performed to illustrate the influence of reliability and latency on the control of autonomous vehicles over fog.

Connected through hyperedge HE-1 (induced by source paper "communication efficient massive uav online path control federated learning meets mean field game theory"):
  with members:
    - "massive autonomous uav path planning a neural network based mean field game theoretic approach"
    - "remote uav online path planning via neural network based opportunistic control"
    - "reinforcement learning for uav attitude control"
    - "massive uav to ground communication and its stable movement control a mean field approach"
    - "autonomous uav navigation using reinforcement learning"
    - "energy efficient uav communication with trajectory optimization"
    - "communication efficient learning of deep networks from decentralized data"

Connected through hyperedge HE-2 (induced by source paper "massive autonomous uav path planning a neural network based mean field game theoretic approach"):
  with members:
    - "wireless network intelligence at the edge"
    - "massive uav to ground communication and its stable movement control a mean field approach"
    - "a tutorial on uavs for wireless networks applications challenges and open problems"
    - "efficient deployment of multiple unmanned aerial vehicles for optimal wireless coverage"

Connected through hyperedge HE-3 (induced by source paper "characterizing task completion latencies in fog computing"):
  with members:
    - "distributed deep neural networks over the cloud the edge and end devices"
    - "update or wait how to keep your data fresh"

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.IT(Information Theory)