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 "efficient redundancy techniques for latency reduction in cloud systems"):
  Abstract: In cloud computing systems, assigning a task to multiple servers and waiting for the earliest copy to finish is an effective method to combat the variability in response time of individual servers, and reduce latency. But adding redundancy may result in higher cost of computing resources, as well as an increase in queueing delay due to higher traffic load. This work helps understand when and how redundancy gives a cost-efficient reduction in latency. For a general task service time distribution, we compare different redundancy strategies in terms of the number of redundant tasks, and time when they are issued and canceled. We get the insight that the log-concavity of the task service time creates a dichotomy of when adding redundancy helps. If the service time distribution is log-convex (i.e. log of the tail probability is convex) then adding maximum redundancy reduces both latency and cost. And if it is log-concave (i.e. log of the tail probability is concave), then less redundancy, and early cancellation of redundant tasks is more effective. Using these insights, we design a general redundancy strategy that achieves a good latency-cost trade-off for an arbitrary service time distribution. This work also generalizes and extends some results in the analysis of fork-join queues.

Includes members:
  Member "using straggler replication to reduce latency in large scale parallel computing extended version":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "optimal server selection for straggler mitigation")
  Member "provably delay efficient data retrieving in storage clouds":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "analyzing the download time of availability codes")
  Member "using straggler replication to reduce latency in large scale parallel computing":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "codenet training large scale neural networks in presence of soft errors")
  Member "efficient task replication for fast response times in parallel computation":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "codenet training large scale neural networks in presence of soft errors")
  Member "when queueing meets coding optimal latency data retrieving scheme in storage clouds":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "delay optimal policies in partial fork join systems with redundancy and random slowdowns")
  Member "when do redundant requests reduce latency":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "straggler resistant distributed matrix computation via coding theory")
  Member "tofec achieving optimal throughput delay trade off of cloud storage using erasure codes":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "optimal load allocation for coded distributed computation in heterogeneous clusters")
  Member "on the delay storage trade off in content download from coded distributed storage systems":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a combinatorial view of the service rates of codes problem its equivalence to fractional matching and its connection with batch codes")

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)