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: "federated scheduling admits no constant speedup factors for constrained deadline dag task systems"
  Abstract: In the federated scheduling approaches in multiprocessor systems, a task either (1) is restricted to execute sequentially on a single processor or (2) has exclusive access to the assigned processors. There have been several positive results to conduct good federated scheduling policies, which have constant speedup factors with respect to any optimal federated scheduling algorithm. This paper answers an open question: "For constrained-deadline task systems with directed acyclic graph (DAG) dependency structures, do federated scheduling policies have a constant speedup factor with respect to any optimal scheduling algorithm?" The answer is "No!" This paper presents an example, which demonstrates that any federated scheduling algorithm has a speedup factor of at least $$\Omega \,(\min \{M, N\})$$Ω(min{M,N}) with respect to any optimal scheduling algorithm, where N is the number of tasks and M is the number of processors.

Connected through hyperedge HE-1 (induced by source paper "dependency graph approach for multiprocessor real time synchronization"):
  with members:
    - "reservation based federated scheduling for parallel real time tasks"
    - "semi federated scheduling of parallel real time tasks on multiprocessors"

Connected through hyperedge HE-2 (induced by source paper "reservation based federated scheduling for parallel real time tasks"):
  with members:
    - "push forward global fixed priority scheduling of arbitrary deadline sporadic task systems"
    - "semi federated scheduling of parallel real time tasks on multiprocessors"
    - "partitioned multiprocessor fixed priority scheduling of sporadic real time tasks"
    - "feasibility analysis in the sporadic dag task model"

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)