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: "new online algorithm for dynamic speed scaling with sleep state"
  Abstract: We consider an energy-efficient scheduling problem where n jobs J 1 , J 2 , ?, J n need to be executed such that the total energy usage by these jobs is minimized while ensuring that each job is finished within its deadline. The processor executing these jobs can be in either active or sleep state at any point of time. The speed of the processor in an active state can be arbitrary. If the processor is running at a speed s ? 0 , the required power P ( s ) is assumed to be equal to s α + g where α 1 , g 0 are constants. On the other hand, the required power is zero when the processor is in the sleep state. However, L 0 amount of wake-up energy is needed to wake-up the processor from the sleep state to the active state.In this paper, we work in an online setting where a job is known only at its arrival time, along with its processing volume and deadline. In such a setting, the currently best-known algorithm by Han et al. (2010) 3] provides a competitive ratio max ? { 4 , 2 + α α } of energy usage. We present a new online algorithm SqOA which provides a competitive ratio max ? { 4 , 2 + ( 2 - 1 / α ) α 2 α - 1 } of energy usage. For α ? 2.34 , the competitive ratio of our algorithm is better than that of any other existing algorithm for this problem.

Connected through hyperedge HE-1 (induced by source paper "green data centers a survey perspectives and future directions"):
  with members:
    - "a fully polynomial time approximation scheme for speed scaling with sleep state"
    - "sleepscale runtime joint speed scaling and sleep states management for power efficient data centers"
    - "throughput maximization in multiprocessor speed scaling"
    - "throughput maximization in the speed scaling setting"
    - "energy efficient scheduling with time and processors eligibility restrictions"
    - "speed scaling on parallel processors with migration"
    - "scalably scheduling power heterogeneous processors"
    - "polynomial time algorithms for minimum energy scheduling"

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.DS(Data Structures and Algorithms)