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: "fog computing principles architectures and applications"
  Abstract: Abstract   The Internet of Everything (IoE) solutions gradually bring every object online, and processing data in a centralized cloud does not scale to requirements of such an environment. This is because there are applications such as health monitoring and emergency response that require low latency, so delay caused by transferring data to the cloud and then back to the application can seriously impact the performance. To this end, Fog computing has emerged, where cloud computing is extended to the edge of the network to decrease the latency and network congestion. Fog computing is a paradigm for managing a highly distributed and possibly virtualized environment that provides compute and network services between sensors and cloud data centers. This chapter provides a background and motivations regarding the emergence of Fog computing, and defines its key characteristics. In addition, a reference architecture for Fog computing is presented, and recent related development and applications are discussed.

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"
    - "big data and fog computing"

Connected through hyperedge HE-2 (induced by source paper "a fog robotics approach to deep robot learning application to object recognition and grasp planning in surface decluttering"):
  with members:
    - "network offloading policies for cloud robotics a learning based approach"
    - "fog robotics for efficient fluent and robust human robot interaction"
    - "closing the sim to real loop adapting simulation randomization with real world experience"
    - "mobile edge computing fog et al a survey and analysis of security threats and challenges"
    - "scanning the internet for ros a view of security in robotics research"
    - "a fog robotic system for dynamic visual servoing"
    - "robot learning in homes improving generalization and reducing dataset bias"
    - "focal loss for dense object detection"

Connected through hyperedge HE-3 (induced by source paper "a systemic iot fog cloud architecture for big data analytics and cyber security systems a review of fog computing"):
  with members:
    - "mobile edge computing fog et al a survey and analysis of security threats and challenges"
    - "fog data enhancing telehealth big data through fog computing"

Connected through hyperedge HE-4 (induced by source paper "fog computing architectures a reference for practitioners"):
  with members:
    - "fog computing survey of trends architectures requirements and research directions"

Connected through hyperedge HE-5 (induced by source paper "dynamic network slicing for scalable fog computing systems with energy harvesting"):
  with members:
    - "distributed optimization for energy efficient fog computing in the tactile internet"
    - "computing resource allocation in three tier iot fog networks a joint optimization approach combining stackelberg game and matching"
    - "sdfog a software defined computing architecture for qos aware service orchestration over edge devices"
    - "response time optimized distributed cloud resource allocation"
    - "from network sharing to multi tenancy the 5g network slice broker"
    - "network slicing games enabling customization in multi tenant networks"
    - "spatial spectrum and energy efficiency of random cellular networks"
    - "energy harvesting wireless communications a review of recent advances"

Connected through hyperedge HE-6 (induced by source paper "fog computing survey of trends architectures requirements and research directions"):
  with members:
    - "fog computing a taxonomy survey and future directions"
    - "fog assisted wiot a smart fog gateway for end to end analytics in wearable internet of things"
    - "fog computing for sustainable smart cities a survey"
    - "demystifying fog computing characterizing architectures applications and abstractions"
    - "fog data enhancing telehealth big data through fog computing"
    - "big data computing and clouds"

Connected through hyperedge HE-7 (induced by source paper "violet a large scale virtual environment for internet of things"):
  with members:
    - "mathbb echo an adaptive orchestration platform for hybrid dataflows across cloud and edge"
    - "demystifying fog computing characterizing architectures applications and abstractions"
    - "riotbench a real time iot benchmark for distributed stream processing platforms"
    - "plug and play bench simplifying big data benchmarking using containers"
    - "distributed scheduling of event analytics across edge and cloud"

Connected through hyperedge HE-8 (induced by source paper "fog computing a taxonomy survey and future directions"):
  with members:
    - "ifogsim a toolkit for modeling and simulation of resource management techniques in internet of things edge and fog computing environments"
    - "fog computing based radio access networks issues and challenges"
    - "user access mode selection in fog computing based radio access networks"
    - "challenges and opportunities in edge computing"

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)