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: "online scheduling on identical machines using srpt"
  Abstract: Due to its optimality on a single machine for the problem of minimizing average flow time, Shortest-Remaining-Processing-Time (\srpt) appears to be the most natural algorithm to consider for the problem of minimizing average flow time on multiple identical machines. It is known that $\srpt$ achieves the best possible competitive ratio on multiple machines up to a constant factor. Using resource augmentation, $\srpt$ is known to achieve total flow time at most that of the optimal solution when given machines of speed $2- \frac{1}{m}$. Further, it is known that $\srpt$'s competitive ratio improves as the speed increases; $\srpt$ is $s$-speed $\frac{1}{s}$-competitive when $s \geq 2- \frac{1}{m}$. #R##N#However, a gap has persisted in our understanding of $\srpt$. Before this work, the performance of $\srpt$ was not known when $\srpt$ is given $(1+\eps)$-speed when $0  0$. We complement this by showing that $\srpt$ is $(1+\eps)$-speed $O(\frac{1}{\eps^2})$-competitive for the objective of minimizing the $\ell_k$-norms of flow time on $m$ identical machines. Both of our results rely on new potential functions that capture the structure of \srpt. Our results, combined with previous work, show that $\srpt$ is the best possible online algorithm in essentially every aspect when migration is permissible.

Connected through hyperedge HE-1 (induced by source paper "online job scheduling with redundancy and opportunistic checkpointing a speedup function based analysis"):
  with members:
    - "task cloning algorithms in a mapreduce cluster with competitive performance bounds"
    - "optimization for speculative execution of multiple jobs in a mapreduce like cluster"
    - "competitive algorithms from competitive equilibria non clairvoyant scheduling under polyhedral constraints"
    - "when queueing meets coding optimal latency data retrieving scheme in storage clouds"
    - "selfishmigrate a scalable algorithm for non clairvoyantly scheduling heterogeneous processors"
    - "when do redundant requests reduce latency"
    - "online primal dual for non linear optimization with applications to speed scaling"

Connected through hyperedge HE-2 (induced by source paper "provably delay efficient data retrieving in storage clouds"):
  with members:
    - "when queueing meets coding optimal latency data retrieving scheme in storage clouds"
    - "on the latency of erasure coded cloud storage systems"
    - "when do redundant requests reduce latency"
    - "tofec achieving optimal throughput delay trade off of cloud storage using erasure codes"
    - "fast cloud pushing the envelope on delay performance of cloud storage with coding"
    - "a solution to the network challenges of data recovery in erasure coded distributed storage systems a study on the facebook warehouse cluster"
    - "on the delay storage trade off in content download from coded distributed storage systems"
    - "the mds queue analysing the latency performance of erasure codes"

Connected through hyperedge HE-3 (induced by source paper "the complexity of scheduling for p norms of flow and stretch"):
  with members:
    - "online primal dual for non linear optimization with applications to speed scaling"
    - "the geometry of scheduling"
    - "longest wait first for broadcast scheduling"

Connected through hyperedge HE-4 (induced by source paper "a simulator for data intensive job scheduling"):
  with members:
    - "practical size based scheduling for mapreduce workloads"
    - "interactive analytical processing in big data systems a cross industry study of mapreduce workloads"

Connected through hyperedge HE-5 (induced by source paper "practical size based scheduling for mapreduce workloads"):
  with members:
    - "interactive analytical processing in big data systems a cross industry study of mapreduce workloads"

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)