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 taxonomy and survey of energy efficient data centers and cloud computing systems"
  Abstract: Traditionally, the development of computing systems has been focused on performance improvements driven by the demand of applications from consumer, scientific and business domains. However, the ever increasing energy consumption of computing systems has started to limit further performance growth due to overwhelming electricity bills and carbon dioxide footprints. Therefore, the goal of the computer system design has been shifted to power and energy efficiency. To identify open challenges in the area and facilitate future advancements it is essential to synthesize and classify the research on power and energy-efficient design conducted to date. In this work we discuss causes and problems of high power / energy consumption, and present a taxonomy of energy-efficient design of computing systems covering the hardware, operating system, virtualization and data center levels. We survey various key works in the area and map them to our taxonomy to guide future design and development efforts. This chapter is concluded with a discussion of advancements identified in energy-efficient computing and our vision on future research directions.

Connected through hyperedge HE-1 (induced by source paper "reinforcement learning based autoscaling of workflows in the cloud a survey"):
  with members:
    - "cmi an online multi objective genetic autoscaler for scientific and engineering workflows in cloud infrastructures with unreliable virtual machines"
    - "a disciplined approach to neural network hyper parameters part 1 learning rate batch size momentum and weight decay"
    - "deep learning a critical appraisal"
    - "a comparison of reinforcement learning techniques for fuzzy cloud auto scaling"
    - "automated cloud provisioning on aws using deep reinforcement learning"
    - "dueling network architectures for deep reinforcement learning"
    - "high performance cloud computing a view of scientific applications"

Connected through hyperedge HE-2 (induced by source paper "decentralization in digital societies a design paradox"):
  with members:
    - "ipfs content addressed versioned p2p file system"

Connected through hyperedge HE-3 (induced by source paper "a deep learning based approach to vm behavior identification in cloud systems"):
  with members:
    - "batch normalization accelerating deep network training by reducing internal covariate shift"
    - "adam a method for stochastic optimization"
    - "autonomic cloud computing open challenges and architectural elements"

Connected through hyperedge HE-4 (induced by source paper "big data meet cyber physical systems a panoramic survey"):
  with members:
    - "information and communications technologies for sustainable development goals state of the art needs and perspectives"
    - "improving the coverage and spectral efficiency of millimeter wave cellular networks using device to device relays"
    - "developing an edge computing platform for real time descriptive analytics"
    - "security and privacy aspects in mapreduce on clouds a survey"
    - "wireless device to device caching networks basic principles and system performance"
    - "social computing for mobile big data"
    - "streaming big data meets backpressure in distributed network computation"
    - "big data caching for networking moving from cloud to edge"

Connected through hyperedge HE-5 (induced by source paper "the internet of things fog and cloud continuum integration and challenges"):
  with members:
    - "fog computing a taxonomy survey and future directions"
    - "network slicing based 5g and future mobile networks mobility resource management and challenges"
    - "mathbb echo an adaptive orchestration platform for hybrid dataflows across cloud and edge"
    - "an iot endpoint system on chip for secure and energy efficient near sensor analytics"
    - "energy efficient resource allocation for mobile edge computation offloading"
    - "from network sharing to multi tenancy the 5g network slice broker"
    - "an internet of things framework for smart energy in buildings designs prototype and experiments"
    - "internet of things iot a vision architectural elements and future directions"

Connected through hyperedge HE-6 (induced by source paper "multiple workflows scheduling in multi tenant distributed systems a taxonomy and future directions"):
  with members:
    - "predictive performance modeling for distributed batch processing using black box monitoring and machine learning"
    - "container solutions for hpc systems a case study of using shifter on blue waters"
    - "task runtime prediction in scientific workflows using an online incremental learning approach"
    - "scalability of vm provisioning systems"
    - "patterns in the chaos a study of performance variation and predictability in public iaas clouds"
    - "monetary cost optimizations for hosting workflow as a service in iaas clouds"
    - "internet of things iot a vision architectural elements and future directions"
    - "a taxonomy of workflow management systems for grid computing"

Connected through hyperedge HE-7 (induced by source paper "extending demand response to tenants in cloud data centers via non intrusive workload flexibility pricing"):
  with members:
    - "reducing electricity demand charge for data centers with partial execution"
    - "optimal power cost management using stored energy in data centers"

Connected through hyperedge HE-8 (induced by source paper "software defined multi cloud computing a vision architectural elements and future directions"):
  with members:
    - "stratos a network aware orchestration layer for virtual middleboxes in clouds"

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)