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: "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.

Connected through hyperedge HE-1 (induced by source paper "erasure codes for distributed storage tight bounds and matching constructions"):
  with members:
    - "explicit msr codes with optimal access optimal sub packetization and small field size for d k 1 k 2 k 3"
    - "a tight rate bound and a matching construction for locally recoverable codes with sequential recovery from any number of multiple erasures"
    - "optimal lrc codes for all lenghts n q"
    - "optimal locally repairable codes of distance 3 and 4 via cyclic codes"
    - "on optimal ternary locally repairable codes"
    - "liquid cloud storage"
    - "rate optimal binary linear locally repairable codes with small availability"
    - "bounds and constructions of codes with all symbol locality and availability"

Connected through hyperedge HE-2 (induced by source paper "a layered architecture for erasure coded consistent distributed storage"):
  with members:
    - "radon repairable atomic data object in networks"
    - "information theoretic lower bounds on the storage cost of shared memory emulation"
    - "storage optimized data atomic algorithms for handling erasures and errors in distributed storage systems"
    - "space bounds for reliable storage fundamental limits of coding"
    - "a coded shared atomic memory algorithm for message passing architectures"
    - "xoring elephants novel erasure codes for big data"
    - "optimal exact regenerating codes for distributed storage at the msr and mbr points via a product matrix construction"
    - "a survey on network codes for distributed storage"

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.IT(Information Theory)