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 "the storage versus repair bandwidth trade off for clustered storage systems"):
  Abstract: We study a generalization of the setting of regenerating codes, motivated by applications to storage systems consisting of clusters of storage nodes. There are    $n$    clusters in total, with    $m$    nodes per cluster. A data file is coded and stored across the    $mn$    nodes, with each node storing    $\alpha $    symbols. For availability of data, we require that the file be retrievable by downloading the entire content from any subset of    $k$    clusters. Nodes represent entities that can fail. We distinguish between intra-cluster and inter-cluster bandwidth (BW) costs during node repair. Node-repair in a cluster is accomplished by downloading    $\beta $    symbols each from any set of    $d$    other clusters, dubbed remote helper clusters, and also up to    $\alpha $    symbols each from any set of    $\ell $    surviving nodes, dubbed local helper nodes, in the host cluster. We first identify the optimal trade-off between storage-overhead and inter-cluster repair-bandwidth under functional repair, and also present optimal exact-repair code constructions for a class of parameters. The new trade-off is strictly better than what is achievable via space-sharing existing coding solutions, whenever    $\ell > 0$   . We then obtain sharp lower bounds on the necessary intra-cluster repair BW to achieve optimal trade-off. Under functional repair, random linear network codes (RLNCs) simultaneously optimize usage of both inter- and intra-cluster repair BW; simulation results based on RLNCs suggest optimality of the bounds on intra-cluster repair-bandwidth. Our bounds reveal the interesting fact that, while it is beneficial to increase the number of local helper nodes    $\ell $    in order to improve the storage-vs-inter-cluster-repair-BW trade-off, increasing    $\ell $    not only increases intra-cluster BW in the host-cluster, but also increases the intra-cluster BW in the remote helper clusters. We also analyze resilience of the clustered storage system against passive eavesdropping by providing file-size bounds and optimal code constructions.

Includes members:
  Member "optimal repair layering for erasure coded data centers from theory to practice":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "explicit constructions of msr codes for clustered distributed storage the rack aware storage model")
  Member "capacity of clustered distributed storage":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "cascade codes for distributed storage systems")
  Member "a note on secure minimum storage regenerating codes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "universally weakly secure coset coding schemes for minimum storage regenerating msr codes")
  Member "architecture aware coding for distributed storage repairable block failure resilient codes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "multi rack distributed data storage networks")
  Member "non homogeneous two rack model for distributed storage systems":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "topology aware cooperative data protection in blockchain based decentralized storage networks")
  Member "capacity and security of heterogeneous distributed storage systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "capacity of distributed storage systems with clusters and separate nodes")
  Member "a realistic distributed storage system the rack model":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "multi rack distributed data storage networks")
  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-8 (induced by source paper "enabling optimal access and error correction for the repair of reed solomon codes")

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)