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 "evaluation of codes with inherent double replication for hadoop"):
  Abstract: In this paper, we evaluate the efficacy, in a Hadoop setting, of two coding schemes, both possessing an inherent double replication of data. The two coding schemes belong to the class of regenerating and locally regenerating codes respectively, and these two classes are representative of recent advances made in designing codes for the efficient storage of data in a distributed setting. In comparison with triple replication, double replication permits a significant reduction in storage overhead, while delivering good MapReduce performance under moderate work loads. The two coding solutions under evaluation here, add only moderately to the storage overhead of double replication, while simultaneously offering reliability levels similar to that of triple replication. #R##N#One might expect from the property of inherent data duplication that the performance of these codes in executing a MapReduce job would be comparable to that of double replication. However, a second feature of this class of code comes into play here, namely that under both coding schemes analyzed here, multiple blocks from the same coded stripe are required to be stored on the same node. This concentration of data belonging to a single stripe negatively impacts MapReduce execution times. However, much of this effect can be undone by simply adding a larger number of processors per node. Further improvements are possible if one tailors the Map task scheduler to the codes under consideration. We present both experimental and simulation results that validate these observations.

Includes members:
  Member "xoring elephants novel erasure codes for big data":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on optimal locally repairable codes and generalized sector disk codes")
  Member "core augmenting regenerating coding based recovery for single and concurrent failures in distributed storage systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "concurrent regenerating codes and scalable application in network storage")
  Member "a solution to the network challenges of data recovery in erasure coded distributed storage systems a study on the facebook warehouse cluster":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "convertible codes efficient conversion of coded data in distributed storage")
  Member "distributed storage codes with repair by transfer and nonachievability of interior points on the storage bandwidth tradeoff":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "enabling optimal access and error correction for the repair of reed solomon codes")
  Member "codes with local regeneration":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "locally recoverable j affine variety codes")
  Member "on the locality of codeword symbols":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a locality based approach for coded computation")

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.IT(Information Theory)