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: "cloud benchmarking for performance"
  Abstract: How can applications be deployed on the cloud to achieve maximum performance? This question has become significant and challenging with the availability of a wide variety of Virtual Machines (VMs) with different performance capabilities in the cloud. The above question is addressed by proposing a six step benchmarking methodology in which a user provides a set of four weights that indicate how important each of the following groups: memory, processor, computation and storage are to the application that needs to be executed on the cloud. The weights along with cloud benchmarking data are used to generate a ranking of VMs that can maximise performance of the application. The rankings are validated through an empirical analysis using two case study applications, the first is a financial risk application and the second is a molecular dynamics simulation, which are both representative of workloads that can benefit from execution on the cloud. Both case studies validate the feasibility of the methodology and highlight that maximum performance can be achieved on the cloud by selecting the top ranked VMs produced by the methodology.

Connected through hyperedge HE-1 (induced by source paper "transferable knowledge for low cost decision making in cloud environments"):
  with members:
    - "cloud brokerage a systematic survey"
    - "unsupervised machine learning for networking techniques applications and research challenges"
    - "daleel simplifying cloud instance selection using machine learning"
    - "patterns in the chaos a study of performance variation and predictability in public iaas clouds"

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

Connected through hyperedge HE-3 (induced by source paper "feasibility of fog computing"):
  with members:
    - "academic cloud computing research five pitfalls and five opportunities"
    - "sla oriented resource provisioning for cloud computing challenges architecture and solutions"

Connected through hyperedge HE-4 (induced by source paper "resource management in fog edge computing a survey"):
  with members:
    - "edge fog cloud a distributed cloud for internet of things computations"
    - "foggy a platform for workload orchestration in a fog computing environment"
    - "a survey on mobile edge computing the communication perspective"
    - "enorm a framework for edge node resource management"
    - "edge as a service towards distributed cloud architectures"
    - "distributed deep neural networks over the cloud the edge and end devices"
    - "dynamic service placement for mobile micro clouds with predicted future costs"
    - "big data caching for networking moving from cloud to edge"

Connected through hyperedge HE-5 (induced by source paper "same same but different a descriptive differentiation of intra cloud iaas services"):
  with members:
    - "daleel simplifying cloud instance selection using machine learning"
    - "patterns in the chaos a study of performance variation and predictability in public iaas clouds"

Connected through hyperedge HE-6 (induced by source paper "a survey and taxonomy of resource optimisation for executing bag of task applications on public clouds"):
  with members:
    - "optex a deadline aware cost optimization model for spark"
    - "managing deadline constrained bag of tasks jobs on hybrid clouds"
    - "budget constrained execution of multiple bag of tasks applications on the cloud"
    - "executing bag of distributed tasks on virtually unlimited cloud resources"
    - "task scheduling on the cloud with hard constraints"
    - "executing bag of distributed tasks on the cloud investigating the trade offs between performance and cost"
    - "patterns in the chaos a study of performance variation and predictability in public iaas clouds"

Connected through hyperedge HE-7 (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"
    - "parallel simulations for analysing portfolios of catastrophic event risk"
    - "on a catalogue of metrics for evaluating commercial cloud services"

Connected through hyperedge HE-8 (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"
    - "location location location data intensive distributed computing in the cloud"
    - "parallel simulations for analysing portfolios of catastrophic event risk"
    - "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)