human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "dynamic provisioning in next generation data centers with on site power production"):
  Abstract: The critical need for clean and economical sources of energy is transforming data centers that are primarily energy consumers to also energy producers. We focus on minimizing the operating costs of next-generation data centers that can jointly optimize the energy supply from on-site generators and the power grid, and the energy demand from servers as well as power conditioning and cooling systems. We formulate the cost minimization problem and present an offline optimal algorithm. For "on-grid" data centers that use only the grid, we devise a deterministic online algorithm that achieves the best possible competitive ratio of $2-\alpha_{s}$, where $\alpha_{s}$ is a normalized look-ahead window size. For "hybrid" data centers that have on-site power generation in addition to the grid, we develop an online algorithm that achieves a competitive ratio of at most \textmd{\normalsize {\small $\frac{P_{\max} (2-\alpha_{s})}{c_{o}+c_{m}/L} [1+2\frac{P_{\max}-c_{o}}{P_{\max}(1+\alpha_{g})}]$}}, where $\alpha_{s}$ and $\alpha_{g}$ are normalized look-ahead window sizes, $P_{\max}$ is the maximum grid power price, and $L$, $c_{o}$, and $c_{m}$ are parameters of an on-site generator. #R##N#Using extensive workload traces from Akamai with the corresponding grid power prices, we simulate our offline and online algorithms in a realistic setting. Our offline (resp., online) algorithm achieves a cost reduction of 25.8% (resp., 20.7%) for a hybrid data center and 12.3% (resp., 7.3%) for an on-grid data center. The cost reductions are quite significant and make a strong case for a joint optimization of energy supply and energy demand in a data center. A hybrid data center provides about 13% additional cost reduction over an on-grid data center representing the additional cost benefits that on-site power generation provides over using the grid alone.

Includes members:
  Member "online energy generation scheduling for microgrids with intermittent energy sources and co generation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "competitive online optimization under inventory constraints")
  Member "energy aware load balancing in content delivery networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a novel communication cost aware load balancing in content delivery networks using honeybee algorithm")
  Member "simple and effective dynamic provisioning for power proportional data centers":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a tale of two metrics simultaneous bounds on competitiveness and regret")
  Member "a taxonomy and survey of energy efficient data centers and cloud computing systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "reinforcement learning based autoscaling of workflows in the cloud a survey")

Question: Please tell me which class the source paper 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.DS(Data Structures and Algorithms)