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: "efficient hybrid inline and out of line deduplication for backup storage"
  Abstract: Backup storage systems often remove redundancy across backups via inline deduplication, which works by referring duplicate chunks of the latest backup to those of existing backups. However, inline deduplication degrades restore performance of the latest backup due to fragmentation, and complicates deletion of ex- pired backups due to the sharing of data chunks. While out-of-line deduplication addresses the problems by forward-pointing existing duplicate chunks to those of the latest backup, it introduces additional I/Os of writing and removing duplicate chunks. We design and implement RevDedup, an efficient hybrid inline and out-of-line deduplication system for backup storage. It applies coarse-grained inline deduplication to remove duplicates of the latest backup, and then fine-grained out-of-line reverse deduplication to remove duplicates from older backups. Our reverse deduplication design limits the I/O overhead and prepares for efficient deletion of expired backups. Through extensive testbed experiments using synthetic and real-world datasets, we show that RevDedup can bring high performance to the backup, restore, and deletion operations, while maintaining high storage efficiency comparable to conventional inline deduplication.

Connected through hyperedge HE-1 (induced by source paper "hpdedup a hybrid prioritized data deduplication mechanism for primary storage in the cloud"):
  with members:
    - "streaming and sublinear approximation of entropy and information distances"

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)