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: "the internet of things fog and cloud continuum integration and challenges"
  Abstract: Abstract   The Internet of Things needs for computing power and storage are expected to remain on the rise in the next decade. Consequently, the amount of data generated by devices at the edge of the network will also grow. While cloud computing has been an established and effective way of acquiring computation and storage as a service to many applications, it may not be suitable to handle the myriad of data from IoT devices and fulfill largely heterogeneous application requirements. Fog computing has been developed to lie between IoT and the cloud, providing a hierarchy of computing power that can collect, aggregate, and process data from/to IoT devices. Combining fog and cloud may reduce data transfers and communication bottlenecks to the cloud and also contribute to reduced latencies, as fog computing resources exist closer to the edge. This paper examines this IoT-Fog-Cloud ecosystem and provides a literature review from different facets of it: how it can be organized, how management is being addressed, and how applications can benefit from it. Lastly, we present challenging issues yet to be addressed in IoT-Fog-Cloud infrastructures.

Connected through hyperedge HE-1 (induced by source paper "fog to cloud and network coded based architecture minimizing data download time for smart mobility"):
  with members:
    - "reliable iot storage minimizing bandwidth use in storage without newcomer nodes"
    - "demystifying fog computing characterizing architectures applications and abstractions"
    - "a survey on network codes for distributed storage"

Connected through hyperedge HE-2 (induced by source paper "fog computing on constrained devices paving the way for the future iot"):
  with members:
    - "deep learning for hate speech detection in tweets"
    - "tensorflow a system for large scale machine learning"

Connected through hyperedge HE-3 (induced by source paper "transformative effects of iot blockchain and artificial intelligence on cloud computing evolution vision trends and open challenges"):
  with members:
    - "healthfog an ensemble deep learning based smart healthcare system for automatic diagnosis of heart diseases in integrated iot and fog computing environments"
    - "a deep learning based approach to vm behavior identification in cloud systems"
    - "edgelens deep learning based object detection in integrated iot fog and cloud computing environments"
    - "bottlenet a deep learning architecture for intelligent mobile cloud computing services"
    - "cloud chaser real time deep learning computer vision on low computing power devices"
    - "a survey on the security of blockchain systems"
    - "container based cluster orchestration systems a taxonomy and future directions"
    - "sustainable cloud computing foundations and future directions"

Connected through hyperedge HE-4 (induced by source paper "impact of distributed processing on power consumption for iot based surveillance applications"):
  with members:
    - "big data analytics for wireless and wired network design a survey"
    - "energy efficient service distribution in internet of things"
    - "patient centric cellular networks optimization using big data analytics"
    - "bounds for energy efficient survivable ip over wdm networks with network coding"
    - "optimized energy aware 5g network function virtualization"

Connected through hyperedge HE-5 (induced by source paper "development of internet of things augmented reality and 5g technologies review"):
  with members:
    - "machine learning for internet of things data analysis a survey"

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)