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 "a utilization model for optimization of checkpoint intervals in distributed stream processing systems"):
  Abstract: State-of-the-art distributed stream processing systems such as Apache Flink and Storm have recently included checkpointing to provide fault-tolerance for stateful applications. This is a necessary eventuality as these systems head into the Exascale regime, and is evidently more efficient than replication as state size grows. However current systems use a nominal value for the checkpoint interval, indicative of assuming roughly 1 failure every 19 days, that does not take into account the salient aspects of the checkpoint process, nor the system scale, which can readily lead to inefficient system operation. To address this shortcoming, we provide a rigorous derivation of utilization -- the fraction of total time available for the system to do useful work -- that incorporates checkpoint interval, failure rate, checkpoint cost, failure detection and restart cost, depth of the system topology and message delay. Our model yields an elegant expression for utilization and provides an optimal checkpoint interval given these parameters, interestingly showing it to be dependent only on checkpoint cost and failure rate. We confirm the accuracy and efficacy of our model through experiments with Apache Flink, where we obtain improvements in system utilization for every case, especially as the system size increases. Our model provides a solid theoretical basis for the analysis and optimization of more elaborate checkpointing approaches.

Includes members:
  Member "checkpointing to minimize completion time for inter dependent parallel processes on volunteer grids":
    also connected through other hyperedges:
      (none)
  Member "mllib machine learning in apache spark":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "multi layer optimizations for end to end data analytics")

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)