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: "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.

Connected through hyperedge HE-1 (induced by source paper "topology aware cooperative data protection in blockchain based decentralized storage networks"):
  with members:
    - "explicit constructions of msr codes for clustered distributed storage the rack aware storage model"
    - "hierarchical coding to enable scalability and flexibility in heterogeneous cloud storage"
    - "deconstructing the blockchain to approach physical limits"
    - "rack aware regenerating codes for data centers"
    - "cooperative repair constructions of optimal mds codes for all admissible parameters"
    - "multi rack distributed data storage networks"
    - "blockchain in internet of things challenges and solutions"
    - "non homogeneous two rack model for distributed storage systems"

Connected through hyperedge HE-2 (induced by source paper "explicit constructions of msr codes for clustered distributed storage the rack aware storage model"):
  with members:
    - "a generic transformation to enable optimal repair in mds codes for distributed storage systems"
    - "rack aware regenerating codes for data centers"
    - "cooperative repair constructions of optimal mds codes for all admissible parameters"
    - "a class of msr codes for clustered distributed storage"
    - "erasure coding for distributed storage an overview"
    - "optimal repair layering for erasure coded data centers from theory to practice"
    - "increasing availability in distributed storage systems via clustering"
    - "a tight lower bound on the sub packetization level of optimal access msr and mds codes"

Connected through hyperedge HE-3 (induced by source paper "capacity of distributed storage systems with clusters and separate nodes"):
  with members:
    - "storage and repair bandwidth tradeoff for distributed storage systems with clusters and separate nodes"
    - "rack aware regenerating codes for data centers"
    - "optimal repair layering for erasure coded data centers from theory to practice"
    - "video streaming in distributed erasure coded storage systems stall duration analysis"
    - "the storage vs repair bandwidth trade off for multiple failures in clustered storage networks"
    - "capacity of clustered distributed storage"
    - "joint latency and cost optimization for erasure coded data center storage"
    - "sprout a functional caching approach to minimize service latency in erasure coded storage"

Connected through hyperedge HE-4 (induced by source paper "repair pipelining for erasure coded storage algorithms and evaluation"):
  with members:
    - "rack aware regenerating codes for data centers"
    - "optimal repair layering for erasure coded data centers from theory to practice"
    - "xoring elephants novel erasure codes for big data"
    - "a solution to the network challenges of data recovery in erasure coded distributed storage systems a study on the facebook warehouse cluster"

Connected through hyperedge HE-5 (induced by source paper "explicit construction of mbr codes for clustered distributed storage"):
  with members:
    - "explicit constructions of msr codes for clustered distributed storage the rack aware storage model"
    - "a class of msr codes for clustered distributed storage"
    - "secure clustered distributed storage against eavesdroppers"
    - "optimal repair layering for erasure coded data centers from theory to practice"
    - "increasing availability in distributed storage systems via clustering"
    - "locality and availability of array codes constructed from subspaces"
    - "capacity of clustered distributed storage"
    - "minimum storage regenerating codes for all parameters"

Connected through hyperedge HE-6 (induced by source paper "explicit constructions of mbr and msr codes for clustered distributed storage"):
  with members:
    - "explicit constructions of msr codes for clustered distributed storage the rack aware storage model"
    - "a class of msr codes for clustered distributed storage"
    - "secure clustered distributed storage against eavesdroppers"
    - "optimal repair layering for erasure coded data centers from theory to practice"
    - "increasing availability in distributed storage systems via clustering"
    - "locality and availability of array codes constructed from subspaces"
    - "capacity of clustered distributed storage"
    - "minimum storage regenerating codes for all parameters"

Connected through hyperedge HE-7 (induced by source paper "rack aware regenerating codes for data centers"):
  with members:
    - "explicit construction of mbr codes for clustered distributed storage"
    - "a class of msr codes for clustered distributed storage"
    - "optimal repair layering for erasure coded data centers from theory to practice"
    - "capacity of clustered distributed storage"
    - "minimum storage regenerating codes for all parameters"
    - "xoring elephants novel erasure codes for big data"
    - "a realistic distributed storage system that minimizes data storage and repair bandwidth"
    - "capacity and security of heterogeneous distributed storage systems"

Connected through hyperedge HE-8 (induced by source paper "a class of msr codes for clustered distributed storage"):
  with members:
    - "optimal repair layering for erasure coded data centers from theory to practice"
    - "increasing availability in distributed storage systems via clustering"
    - "capacity of clustered distributed storage"
    - "minimum storage regenerating codes for all parameters"
    - "explicit constructions of high rate mds array codes with optimal repair bandwidth"
    - "codes between mbr and msr points with exact repair property"
    - "a family of optimal locally recoverable codes"
    - "optimal locally repairable codes and connections to matroid theory"

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)