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: "all one needs to know about fog computing and related edge computing paradigms a complete survey"
  Abstract: Abstract   With the Internet of Things (IoT) becoming part of our daily life and our environment, we expect rapid growth in the number of connected devices. IoT is expected to connect billions of devices and humans to bring promising advantages for us. With this growth, fog computing, along with its related edge computing paradigms, such as multi-access edge computing (MEC) and cloudlet, are seen as promising solutions for handling the large volume of security-critical and time-sensitive data that is being produced by the IoT. In this paper, we first provide a tutorial on fog computing and its related computing paradigms, including their similarities and differences. Next, we provide a taxonomy of research topics in fog computing, and through a comprehensive survey, we summarize and categorize the efforts on fog computing and its related computing paradigms. Finally, we provide challenges and future directions for research in fog computing.

Connected through hyperedge HE-1 (induced by source paper "fog computing systems state of the art research issues and future trends"):
  with members:
    - "5g network slicing using sdn and nfv a survey of taxonomy architectures and future challenges"
    - "a roadmap toward the resilient internet of things for cyber physical systems"
    - "game theory for multi access edge computing survey use cases and future trends"
    - "a blockchain enabled trustless crowd intelligence ecosystem on mobile edge computing"
    - "machine learning for resource management in cellular and iot networks potentials current solutions and open challenges"
    - "mitigating jamming attacks using energy harvesting"
    - "game theoretical modelling of network cybersecurity"
    - "fundamental concepts of cyber resilience introduction and overview"

Connected through hyperedge HE-2 (induced by source paper "energy efficient distributed processing for iot"):
  with members:
    - "service embedding in iot networks"
    - "patient centric cellular networks optimization using big data analytics"
    - "energy efficient iot virtualization framework with peer to peer networking and processing"
    - "optimized energy aware 5g network function virtualization"
    - "allocation of heterogeneous resources of an iot device to flexible services"

Connected through hyperedge HE-3 (induced by source paper "maintaining data integrity in fog computing based critical infrastructure systems"):
  with members:
    - "fog computing a taxonomy survey and future directions"
    - "fog computing for sustainable smart cities a survey"

Connected through hyperedge HE-4 (induced by source paper "embedded deep learning in ophthalmology making ophthalmic imaging smarter"):
  with members:
    - "deep ehr a survey of recent advances in deep learning techniques for electronic health record ehr analysis"
    - "predicting cardiovascular risk factors in retinal fundus photographs using deep learning"
    - "the intelligent icu pilot study using artificial intelligence technology for autonomous patient monitoring"
    - "towards safe deep learning accurately quantifying biomarker uncertainty in neural network predictions"
    - "towards efficient convolutional neural network for domain specific applications on fpga"
    - "an unsupervised learning model for deformable medical image registration"
    - "a deep learning approach to denoise optical coherence tomography images of the optic nerve head"
    - "plan3d viewpoint and trajectory optimization for aerial multi view stereo reconstruction"

Connected through hyperedge HE-5 (induced by source paper "guardians of the deep fog failure resilient dnn inference from edge to cloud"):
  with members:
    - "wireless network intelligence at the edge"
    - "edge intelligence on demand deep learning model co inference with device edge synergy"
    - "adaptive federated learning in resource constrained edge computing systems"
    - "horovod fast and easy distributed deep learning in tensorflow"
    - "distributed deep neural networks over the cloud the edge and end devices"
    - "online placement of multi component applications in edge computing environments"
    - "deepiot compressing deep neural network structures for sensing systems with a compressor critic framework"
    - "tensorflow a system for large scale machine learning"

Connected through hyperedge HE-6 (induced by source paper "fog computing applications taxonomy and requirements"):
  with members:
    - "fog computing a taxonomy survey and future directions"
    - "fog computing survey of trends architectures requirements and research directions"
    - "a survey of state management in big data processing systems"
    - "foglearn leveraging fog based machine learning for smart system big data analytics"
    - "understanding performance of edge content caching for mobile video streaming"
    - "sdfog a software defined computing architecture for qos aware service orchestration over edge devices"
    - "decentralized computation offloading game for mobile cloud computing"
    - "long range communications in unlicensed bands the rising stars in the iot and smart city scenarios"

Connected through hyperedge HE-7 (induced by source paper "ecomobifog design and dynamic optimization of a 5g mobile fog cloud multi tier ecosystem for the real time distributed execution of stream applications"):
  with members:
    - "fog supported delay constrained energy saving live migration of vms over multipath tcp ip 5g connections"
    - "fog computing a taxonomy survey and future directions"
    - "a survey on mobile edge computing the communication perspective"
    - "mobile edge computing a survey on architecture and computation offloading"
    - "multipath tcp analysis design and implementation"
    - "online admission control and embedding of service chains"

Connected through hyperedge HE-8 (induced by source paper "industrial internet of things iiot applications of edge and fog computing a review and future directions"):
  with members:
    - "fog computing applications taxonomy and requirements"
    - "fog computing a taxonomy survey and future directions"
    - "mobile edge computing fog et al a survey and analysis of security threats and challenges"
    - "internet of things iot a vision architectural elements and future directions"

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)