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 a catalogue of metrics for evaluating commercial cloud services"
  Abstract: Given the continually increasing amount of commercial Cloud services in the market, evaluation of different services plays a significant role in cost-benefit analysis or decision making for choosing Cloud Computing. In particular, employing suitable metrics is essential in evaluation implementations. However, to the best of our knowledge, there is not any systematic discussion about metrics for evaluating Cloud services. By using the method of Systematic Literature Review (SLR), we have collected the de facto metrics adopted in the existing Cloud services evaluation work. The collected metrics were arranged following different Cloud service features to be evaluated, which essentially constructed an evaluation metrics catalogue, as shown in this paper. This metrics catalogue can be used to facilitate the future practice and research in the area of Cloud services evaluation. Moreover, considering metrics selection is a prerequisite of benchmark selection in evaluation implementations, this work also supplements the existing research in benchmarking the commercial Cloud services.

Connected through hyperedge HE-1 (induced by source paper "defog fog computing benchmarks"):
  with members:
    - "cloud benchmarking for maximising performance of scientific applications"
    - "cavbench a benchmark suite for connected and autonomous vehicles"
    - "yolov3 an incremental improvement"
    - "edgebench benchmarking edge computing platforms"
    - "enorm a framework for edge node resource management"
    - "doclite a docker based lightweight cloud benchmarking tool"
    - "challenges and opportunities in edge computing"
    - "container based cloud virtual machine benchmarking"

Connected through hyperedge HE-2 (induced by source paper "cloud benchmarking for maximising performance of scientific applications"):
  with members:
    - "cloud benchmarking for performance"
    - "are clouds ready to accelerate ad hoc financial simulations"
    - "parallel simulations for analysing portfolios of catastrophic event risk"

Connected through hyperedge HE-3 (induced by source paper "doknowme towards a domain knowledge driven methodology for performance evaluation"):
  with members:
    - "on evaluating commercial cloud services a systematic review"
    - "boosting metrics for cloud services evaluation the last mile of using benchmark suites"
    - "a factor framework for experimental design for performance evaluation of commercial cloud services"

Connected through hyperedge HE-4 (induced by source paper "on evaluating commercial cloud services a systematic review"):
  with members:
    - "towards a taxonomy of performance evaluation of commercial cloud services"
    - "a factor framework for experimental design for performance evaluation of commercial cloud services"
    - "cloud computing and grid computing 360 degree compared"

Connected through hyperedge HE-5 (induced by source paper "doclite a docker based lightweight cloud benchmarking tool"):
  with members:
    - "cloud services brokerage a survey and research roadmap"
    - "analysis of docker security"
    - "an introduction to docker for reproducible research with examples from the r environment"
    - "academic cloud computing research five pitfalls and five opportunities"
    - "cloud benchmarking for performance"
    - "parallel simulations for analysing portfolios of catastrophic event risk"

Connected through hyperedge HE-6 (induced by source paper "container based cloud virtual machine benchmarking"):
  with members:
    - "analysis of docker security"
    - "an introduction to docker for reproducible research with examples from the r environment"
    - "optimal deployment of geographically distributed workflow engines on the cloud"
    - "cloud benchmarking for performance"
    - "location location location data intensive distributed computing in the cloud"
    - "parallel simulations for analysing portfolios of catastrophic event risk"

Connected through hyperedge HE-7 (induced by source paper "patterns in the chaos a study of performance variation and predictability in public iaas clouds"):
  with members:
    - "jcloudscale closing the gap between iaas and paas"
    - "early observations on performance of google compute engine for scientific computing"
    - "reliability of computational experiments on virtualised hardware"
    - "cost of virtual machine live migration in clouds a performance evaluation"

Connected through hyperedge HE-8 (induced by source paper "cloud benchmarking for performance"):
  with members:
    - "parallel simulations for analysing portfolios of catastrophic event risk"

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)