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: "an empirical study of the repair performance of novel coding schemes for networked distributed storage systems"
  Abstract: Erasure coding techniques are getting integrated in networked distributed storage systems as a way to provide fault-tolerance at the cost of less storage overhead than traditional replication. Redundancy is maintained over time through repair mechanisms, which may entail large network resource overheads. In recent years, several novel codes tailor-made for distributed storage have been proposed to optimize storage overhead and repair, such as Regenerating Codes that minimize the per repair traffic, or Self-Repairing Codes which minimize the number of nodes contacted per repair. Existing studies of these coding techniques are however predominantly theoretical, under the simplifying assumption that only one object is stored. They ignore many practical issues that real systems must address, such as data placement, de/correlation of multiple stored objects, or the competition for limited network resources when multiple objects are repaired simultaneously. This paper empirically studies the repair performance of these novel storage centric codes with respect to classical erasure codes by simulating realistic scenarios and exploring the interplay of code parameters, failure characteristics and data placement with respect to the trade-offs of bandwidth usage and speed of repairs.

Connected through hyperedge HE-1 (induced by source paper "an overview of codes tailor made for better repairability in networked distributed storage systems"):
  with members:
    - "storage codes coding rate and repair locality"
    - "on locality in distributed storage systems"
    - "cooperative regenerating codes"
    - "mds array codes with optimal rebuilding"
    - "self repairing codes for distributed storage a projective geometric construction"
    - "on the locality of codeword symbols"
    - "cooperative regenerating codes for distributed storage systems"
    - "homomorphic self repairing codes for agile maintenance of distributed storage systems"

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.DC(Distributed, Parallel, and Cluster Computing)