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: "an optimal randomized online algorithm for reordering buffer management"
  Abstract: We give an $O(\log\log k)$-competitive randomized online algorithm for reordering buffer management, where $k$ is the buffer size. Our bound matches the lower bound of Adamaszek et al. (STOC 2011). Our algorithm has two stages which are executed online in parallel. The first stage computes deterministically a feasible fractional solution to an LP relaxation for reordering buffer management. The second stage "rounds" using randomness the fractional solution. The first stage is based on the online primal-dual schema, combined with a dual fitting argument. As multiplicative weights steps and dual fitting steps are interleaved and in some sense conflicting, combining them is challenging. We also note that we apply the primal-dual schema to a relaxation with mixed packing and covering constraints. We pay the $O(\log\log k)$ competitive factor for the gap between the computed LP solution and the optimal LP solution. The second stage gives an online algorithm that converts the LP solution to an integral solution, while increasing the cost by an O(1) factor. This stage generalizes recent results that gave a similar approximation factor for rounding the LP solution, albeit using an offline rounding algorithm.

Connected through hyperedge HE-1 (induced by source paper "online service with delay"):
  with members:
    - "online matching haste makes waste"
    - "tsp with time windows and service time"
    - "a bicriteria approximation for the reordering buffer problem"
    - "approximation algorithms for orienteering with time windows"
    - "the k server dual and loose competitiveness for paging"
    - "competitive paging algorithms"

Connected through hyperedge HE-2 (induced by source paper "stochastic dominance and the bijective ratio of online algorithms"):
  with members:
    - "relative worst order analysis a survey"
    - "a comparison of performance measures for online algorithms"
    - "on line file caching"
    - "on line paging against adversarially biased random inputs"
    - "the k server dual and loose competitiveness for paging"

Connected through hyperedge HE-3 (induced by source paper "run generation revisited what goes up may or may not come down"):
  with members:
    - "a constant factor approximation algorithm for reordering buffer management"

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)