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: "on using micro clouds to deliver the fog"
  Abstract: Cloud computing has demonstrated itself to be a scalable and cost-efficient solution for many real-world applications. However, its modus operandi is not ideally suited to resource-constrained environments that are characterized by limited network bandwidth and high latencies. With the increasing proliferation and sophistication of edge devices, the idea of fog computing proposes to offload some of the computation to the edge. To this end, micro-clouds---which are modular and portable assemblies of small single-board computers---have started to gain attention as infrastructures to support fog computing by offering isolated resource provisioning at the edge in a cost-effective way. We investigate the feasibility and readiness of micro-clouds for delivering the vision of fog computing. Through a number of experiments, we showcase the potential of micro-clouds formed by collections of Raspberry Pi computers to host a range of fog-related applications, particularly for locations where there is limited network bandwidths and long latencies.

Connected through hyperedge HE-1 (induced by source paper "optimizing deep learning inference on embedded systems through adaptive model selection"):
  with members:
    - "characterizing scalability of sparse matrix vector multiplications on phytium ft 2000"
    - "transferable knowledge for low cost decision making in cloud environments"
    - "rectified decision trees towards interpretability compression and empirical soundness"
    - "the university of cambridge s machine translation systems for wmt18"
    - "multi representation ensembles and delayed sgd updates improve syntax based nmt"
    - "an analysis of deep neural network models for practical applications"
    - "fake it till you make it fishing for catfishes"
    - "quantization and training of neural networks for efficient integer arithmetic only inference"

Connected through hyperedge HE-2 (induced by source paper "all one needs to know about fog computing and related edge computing paradigms a complete survey"):
  with members:
    - "pcamp performance comparison of machine learning packages on the edges"
    - "are fpgas suitable for edge computing"
    - "cabaret leveraging recommendation systems for mobile edge caching"
    - "edge intelligence on demand deep learning model co inference with device edge synergy"
    - "fog computing a taxonomy survey and future directions"
    - "data analytics service composition and deployment on edge devices"
    - "live service migration in mobile edge clouds"
    - "on reducing iot service delay via fog offloading"

Connected through hyperedge HE-3 (induced by source paper "open source rans in practice an over the air deployment for 5g mec"):
  with members:
    - "micro operator driven local 5g network architecture for industrial internet"
    - "tinylte lightweight ad hoc deployable cellular network for vehicular communication"
    - "end to end simulation of 5g mmwave networks"
    - "fog computing based radio access networks issues and challenges"
    - "srslte an open source platform for lte evolution and experimentation"
    - "performance evaluation of microservices architectures using containers"
    - "migrating to cloud native architectures using microservices an experience report"

Connected through hyperedge HE-4 (induced by source paper "flexngia a flexible internet architecture for the next generation tactile internet"):
  with members:
    - "on improving service chains survivability through efficient backup provisioning"
    - "price and performance of cloud hosted virtual network functions analysis and future challenges"
    - "opportunistic edge computing concepts opportunities and research challenges"
    - "charting an intent driven network"

Connected through hyperedge HE-5 (induced by source paper "iotnetsim a modelling and simulation platform for end to end iot services and networking"):
  with members:
    - "the design and deployment of an end to end iot infrastructure for the natural environment"
    - "modeling and simulation of scalable cloud computing environments and the cloudsim toolkit challenges and opportunities"

Connected through hyperedge HE-6 (induced by source paper "research challenges in nextgen service orchestration"):
  with members:
    - "mobile edge computing fog et al a survey and analysis of security threats and challenges"
    - "managing service heterogeneity using osmotic computing"
    - "a comparison of reinforcement learning techniques for fuzzy cloud auto scaling"
    - "mobile cloud business process management system for the internet of things a survey"
    - "enorm a framework for edge node resource management"
    - "occupy the cloud distributed computing for the 99"
    - "improving spark application throughput via memory aware task co location a mixture of experts approach"
    - "daleel simplifying cloud instance selection using machine learning"

Connected through hyperedge HE-7 (induced by source paper "opportunistic edge computing concepts opportunities and research challenges"):
  with members:
    - "mobile edge computing fog et al a survey and analysis of security threats and challenges"
    - "a survey on mobile edge computing the communication perspective"
    - "mobile edge computing a survey on architecture and computation offloading"
    - "a view of fog computing from networking perspective"
    - "fog networking an overview on research opportunities"

Connected through hyperedge HE-8 (induced by source paper "next generation cloud computing new trends and research directions"):
  with members:
    - "occupy the cloud distributed computing for the 99"
    - "multi tenant virtual gpus for optimising performance of a financial risk application"
    - "big graph search challenges and techniques"
    - "cloudrone micro clouds in the sky"
    - "cloud services brokerage a survey and research roadmap"
    - "acceleration as a service exploiting virtualised gpus for a financial application"
    - "big data computing and clouds"
    - "sla oriented resource provisioning for cloud computing challenges architecture and solutions"

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)