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: "a factor framework for experimental design for performance evaluation of commercial cloud services"
  Abstract: Given the diversity of commercial Cloud services, performance evaluations of candidate services would be crucial and beneficial for both service customers (e.g. cost-benefit analysis) and providers (e.g. direction of service improvement). Before an evaluation implementation, the selection of suitable factors (also called parameters or variables) plays a prerequisite role in designing evaluation experiments. However, there seems a lack of systematic approaches to factor selection for Cloud services performance evaluation. In other words, evaluators randomly and intuitively concerned experimental factors in most of the existing evaluation studies. Based on our previous taxonomy and modeling work, this paper proposes a factor framework for experimental design for performance evaluation of commercial Cloud services. This framework capsules the state-of-the-practice of performance evaluation factors that people currently take into account in the Cloud Computing domain, and in turn can help facilitate designing new experiments for evaluating Cloud services.

Connected through hyperedge HE-1 (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"
    - "on a catalogue of metrics for evaluating commercial cloud services"

Connected through hyperedge HE-2 (induced by source paper "on evaluating commercial cloud services a systematic review"):
  with members:
    - "on a catalogue of metrics for evaluating commercial cloud services"
    - "towards a taxonomy of performance evaluation of commercial cloud services"
    - "cloud computing and grid computing 360 degree compared"

Connected through hyperedge HE-3 (induced by source paper "a survey on modeling energy consumption of cloud applications deconstruction state of the art and trade off debates"):
  with members:
    - "on evaluating commercial cloud services a systematic review"
    - "optimization of radio and computational resources for energy efficiency in latency constrained application offloading"

Connected through hyperedge HE-4 (induced by source paper "performance overhead comparison between hypervisor and container based virtualization"):
  with members:
    - "doknowme towards a domain knowledge driven methodology for performance evaluation"
    - "towards a taxonomy of performance evaluation of commercial cloud services"

Connected through hyperedge HE-5 (induced by source paper "early observations on performance of google compute engine for scientific computing"):
  with members:
    - "on a catalogue of metrics for evaluating commercial cloud services"
    - "towards a taxonomy of performance evaluation of commercial cloud services"

Connected through hyperedge HE-6 (induced by source paper "boosting metrics for cloud services evaluation the last mile of using benchmark suites"):
  with members:
    - "on a catalogue of metrics for evaluating commercial cloud services"

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)