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: "speed scaling on parallel processors with migration"
  Abstract: We study the problem of scheduling a set of jobs with release dates, deadlines and processing requirements (or works), on parallel speed-scaled processors so as to minimize the total energy consumption. We consider that both preemption and migration of jobs are allowed. An exact polynomial-time algorithm has been proposed for this problem, which is based on the Ellipsoid algorithm. Here, we formulate the problem as a convex program and we propose a simpler polynomial-time combinatorial algorithm which is based on a reduction to the maximum flow problem. Our algorithm runs in $O(nf(n)logP)$ time, where $n$ is the number of jobs, $P$ is the range of all possible values of processors' speeds divided by the desired accuracy and $f(n)$ is the complexity of computing a maximum flow in a layered graph with O(n) vertices. Independently, Albers et al. \cite{AAG11} proposed an $O(n^2f(n))$-time algorithm exploiting the same relation with the maximum flow problem. We extend our algorithm to the multiprocessor speed scaling problem with migration where the objective is the minimization of the makespan under a budget of energy.

Connected through hyperedge HE-1 (induced by source paper "green data centers a survey perspectives and future directions"):
  with members:
    - "new online algorithm for dynamic speed scaling with sleep state"
    - "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"
    - "scalably scheduling power heterogeneous processors"
    - "polynomial time algorithms for minimum energy scheduling"

Connected through hyperedge HE-2 (induced by source paper "speed scaling with no preemptions"):
  with members:
    - "energy efficient scheduling and routing via randomized rounding"
    - "throughput maximization in the speed scaling setting"
    - "power aware scheduling for makespan and flow"

Connected through hyperedge HE-3 (induced by source paper "energy efficient scheduling and routing via randomized rounding"):
  with members:
    - "energy efficient scheduling of mapreduce jobs"
    - "online primal dual for non linear optimization with applications to speed scaling"
    - "santa claus schedules jobs on unrelated machines"

Connected through hyperedge HE-4 (induced by source paper "throughput maximization in multiprocessor speed scaling"):
  with members:
    - "energy efficient scheduling and routing via randomized rounding"
    - "throughput maximization in the speed scaling setting"
    - "profitable scheduling on multiple speed scalable processors"

Connected through hyperedge HE-5 (induced by source paper "energy efficient scheduling with time and processors eligibility restrictions"):
  with members:
    - "reclaiming the energy of a schedule models and algorithms"

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)