human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "online job scheduling with redundancy and opportunistic checkpointing a speedup function based analysis"):
  Abstract: In a large-scale computing cluster, the job completions can be substantially delayed due to two sources of variability, namely, variability in the job size and that in the machine service capacity. To tackle this issue, existing works have proposed various scheduling algorithms which exploit redundancy wherein a job runs on multiple servers until the first completes. In this paper, we explore the impact of variability in the machine service capacity and adopt a rigorous analytical approach to design scheduling algorithms using redundancy and checkpointing. We design several online scheduling algorithms which can dynamically vary the number of redundant copies for jobs. We also provide new theoretical performance bounds for these algorithms in terms of the overall job flowtime by introducing the notion of a speedup function, based on which a novel potential function can be defined to enable the corresponding competitive ratio analysis. In particular, by adopting the online primal-dual fitting approach, we prove that our SRPT+R Algorithm in a non-multitasking cluster is $(1+\epsilon)$-speed, $\ O(\frac{1}{\epsilon})$-competitive. We also show that our proposed Fair+R and LAPS+R($\beta$) Algorithms for a multitasking cluster are $(4+\epsilon)$-speed, $\ O(\frac{1}{\epsilon})$-competitive and {($2 + 2\beta + 2\epsilon)$-speed $O(\frac{1}{\beta \epsilon})$-competitive} respectively. We demonstrate via extensive simulations that our proposed algorithms can significantly reduce job flowtime under both the non-multitasking and multitasking modes.

Includes members:
  Member "task cloning algorithms in a mapreduce cluster with competitive performance bounds":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "client side straggler aware i o scheduler for object based parallel file systems")
  Member "optimization for speculative execution of multiple jobs in a mapreduce like cluster":
    also connected through other hyperedges:
      (none)
  Member "competitive algorithms from competitive equilibria non clairvoyant scheduling under polyhedral constraints":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "dynamic weighted fairness with minimal disruptions")
  Member "when queueing meets coding optimal latency data retrieving scheme in storage clouds":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "delay optimal policies in partial fork join systems with redundancy and random slowdowns")
  Member "selfishmigrate a scalable algorithm for non clairvoyantly scheduling heterogeneous processors":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a unifying optimal control framework for online job scheduling with general cost functions")
  Member "when do redundant requests reduce latency":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "straggler resistant distributed matrix computation via coding theory")
  Member "online primal dual for non linear optimization with applications to speed scaling":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "station assignment with reallocation")
  Member "online scheduling on identical machines using srpt":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "provably delay efficient data retrieving in storage clouds")

Question: Please tell me which class the source paper 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.DC(Distributed, Parallel, and Cluster Computing)