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: "big data and fog computing"
  Abstract: Fog computing serves as a computing layer that sits between the edge devices and the cloud in the network topology. They have more compute capacity than the edge but much less so than cloud data centers. They typically have high uptime and always-on Internet connectivity. Applications that make use of the fog can avoid the network performance limitation of cloud computing while being less resource constrained than edge computing. As a result, they offer a useful balance of the current paradigms. This article explores various aspects of fog computing in the context of big data.

Connected through hyperedge HE-1 (induced by source paper "characterizing application scheduling on edge fog and cloud computing resources"):
  with members:
    - "violet a large scale virtual environment for internet of things"
    - "adaptive energy aware scheduling of dynamic event analytics across edge and cloud resources"
    - "slaq quality driven scheduling for distributed machine learning"
    - "arm wrestling with big data a study of commodity arm64 server for big data workloads"
    - "a manifesto for future generation cloud computing research directions for the next decade"
    - "demystifying fog computing characterizing architectures applications and abstractions"
    - "mobile edge computing a survey on architecture and computation offloading"
    - "distributed scheduling of event analytics across edge and cloud"

Connected through hyperedge HE-2 (induced by source paper "a scalable framework for distributed object tracking across a many camera network"):
  with members:
    - "boxcars improving fine grained recognition of vehicles using 3 d bounding boxes in traffic surveillance"
    - "operator in the loop deep sequential multi camera feature fusion for person re identification"
    - "rexcam resource efficient cross camera video analytics at enterprise scale"
    - "an analysis of deep neural network models for practical applications"
    - "inception v4 inception resnet and the impact of residual connections on learning"
    - "yolo9000 better faster stronger"
    - "tensorflow a system for large scale machine learning"
    - "deep residual learning for image recognition"

Connected through hyperedge HE-3 (induced by source paper "fog assisted cloud models for smart grid architectures comparison study and optimal deployment"):
  with members:
    - "fog computing for sustainable smart cities a survey"
    - "focan a fog supported smart city network architecture for management of applications in the internet of everything environments"
    - "fog assisted operational cost reduction for cloud data centers"

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.DC(Distributed, Parallel, and Cluster Computing)