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: "feasibility of fog computing"
  Abstract: As billions of devices get connected to the Internet, it will not be sustainable to use the cloud as a centralised server. The way forward is to decentralise computations away from the cloud towards the edge of the network closer to the user. This reduces the latency of communication between a user device and the cloud, and is the premise of 'fog computing' defined in this paper. The aim of this paper is to highlight the feasibility and the benefits in improving the Quality-of-Service and Experience by using fog computing. For an online game use-case, we found that the average response time for a user is improved by 20% when using the edge of the network in comparison to using a cloud-only model. It was also observed that the volume of traffic between the edge and the cloud server is reduced by over 90% for the use-case. The preliminary results highlight the potential of fog computing in achieving a sustainable computing model and highlights the benefits of integrating the edge of the network into the computing ecosystem.

Connected through hyperedge HE-1 (induced by source paper "context aware distribution of fog applications using deep reinforcement learning"):
  with members:
    - "defog fog computing benchmarks"
    - "joint communication computation caching and control in big data multi access edge computing"
    - "online learning for offloading and autoscaling in energy harvesting mobile edge computing"
    - "enorm a framework for edge node resource management"
    - "fog radio access networks mobility management interference mitigation and resource optimization"
    - "a survey and taxonomy of resource optimisation for executing bag of task applications on public clouds"
    - "challenges and opportunities in edge computing"
    - "decentralized computation offloading game for mobile cloud computing"

Connected through hyperedge HE-2 (induced by source paper "dyverse dynamic vertical scaling in multi tenant edge environments"):
  with members:
    - "performance estimation of container based cloud to fog offloading"
    - "defog fog computing benchmarks"
    - "realizing edge marketplaces challenges and opportunities"
    - "a survey on mobile edge computing the communication perspective"
    - "enorm a framework for edge node resource management"
    - "joint subcarrier and cpu time allocation for mobile edge computing"
    - "dynamic computation offloading for mobile edge computing with energy harvesting devices"
    - "energy efficient resource allocation for mobile edge computation offloading"

Connected through hyperedge HE-3 (induced by source paper "optimal edge user allocation in edge computing with variable sized vector bin packing"):
  with members:
    - "efficient multi user computation offloading for mobile edge cloud computing"

Connected through hyperedge HE-4 (induced by source paper "focan a fog supported smart city network architecture for management of applications in the internet of everything environments"):
  with members:
    - "fog computing for sustainable smart cities a survey"
    - "fog data enhancing telehealth big data through fog 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)