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 "optimal systematic distributed storage codes with fast encoding"):
  Abstract: Erasure codes are being increasingly used in distributed-storage systems in place of data-replication, since they provide the same level of reliability with much lower storage overhead. We consider the problem of constructing explicit erasure codes for distributed storage with the following desirable properties motivated by practice: (i) Maximum-Distance-Separable (MDS): to provide maximal reliability at minimum storage overhead, (ii) Optimal repair-bandwidth: to minimize the amount of data needed to be transferred to repair a failed node from remaining ones, (iii) Flexibility in repair: to allow maximal flexibility in selecting subset of nodes to use for repair, which includes not requiring that all surviving nodes be used for repair, (iv) Systematic Form: to ensure that the original data exists in uncoded form, and (v) Fast encoding: to minimize the cost of generating encoded data (enabled by a sparse generator matrix). #R##N#This paper presents the first explicit code construction which theoretically guarantees all the five desired properties simultaneously. Our construction builds on a powerful class of codes called Product-Matrix (PM) codes. PM codes satisfy properties (i)-(iii), and either (iv) or (v), but not both simultaneously. Indeed, native PM codes have inherent structure that leads to sparsity, but this structure is destroyed when the codes are made systematic. We first present an analytical framework for understanding the interaction between the design of PM codes and the systematic property. Using this framework, we provide an explicit code construction that simultaneously achieves all the above desired properties. We also present general ways of transforming existing storage and repair optimal codes to enable fast encoding through sparsity. In practice, such sparse codes result in encoding speedup by a factor of about 4 for typical parameters.

Includes members:
  Member "fast product matrix regenerating codes":
    also connected through other hyperedges:
      (none)
  Member "generalization of rashmi shah kumar minimum storage regenerating codes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "information theoretically secure erasure codes for distributed storage")
  Member "xoring elephants novel erasure codes for big data":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on optimal locally repairable codes and generalized sector disk codes")
  Member "when do redundant requests reduce latency":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "straggler resistant distributed matrix computation via coding theory")
  Member "zigzag codes mds array codes with optimal rebuilding":
    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 "fast cloud pushing the envelope on delay performance of cloud storage with coding":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a combinatorial view of the service rates of codes problem its equivalence to fractional matching and its connection with batch codes")
  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-6 (induced by source paper "convertible codes efficient conversion of coded data in distributed storage")
  Member "regenerating codes a system perspective":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "alpha entanglement codes practical erasure codes to archive data in unreliable environments")

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)