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 "erasure codes with simplex locality"):
  Abstract: Abstract—We focus on erasure codes for distributed storage.The distributed storage setting imposes locality requirementsbecause of easy repair demands on the decoder. We ﬁrstestablish the characterization of various locality properties interms of the generator matrix of the code. These lead to boundson locality and notions of optimality. We then examine thelocality properties of a family of nonbinary codes with simplexstructure. We investigate their optimality and design seve raleasy repair decoding methods. In particular, we show that anycorrectable erasure pattern can be solved by easy repair. I. I NTRODUCTION Several classical coding techniques (such as Reed-Solomon erasure codes) are extensively used for data storage,most successfully applied to storage in RAID systems andmagnetic recording (see [2]). However, due to the fast-growing demand for large-scale data storage, it would beimpossible or extremely expensive to build single piecesof hardware with enough storage capabilities to store theenormous volume of data that is being generated. Hence, newclasses of storage technology have emerged using the idea ofdistributing data across multiple nodes which are intercon-nected over a network, as we witness in some peer-to-peer(P2P) storage systems [3] and data centers [4] that comprisethe backbone infrastructure of cloud computing. We call suchsystems Networked Distributed Storage Systems (NDSS).A fundamental issue that arises in this context is theso-called Repair Problem: how to maintain the encodeddata when failures (node erasures) occur. When a storagenode fails, information that was stored in the node is nolonger accessible. As a remedy a node is then added tothe system to replace the failed node. The added nodedownloads data from a set of appropriate and accessiblenodes to recover the information stored in the failed node.This is called node repair. To assess the performance ofthis repair process, there are several metrics that can beconsidered: storage cost, measured as the amount of datastored in the node, repair bandwidth, measured as the totalnumber of bits communicated in the network for each repairand locality, measured as the number of nodes needed foreach repair. For instance, (n,k)maximum distance separable(MDS) codes are optimal in terms of storage cost sinceany k nodes contain the minimum amount of informationrequired to recover the original data. However, to repair one

Includes members:
  Member "a family of optimal locally recoverable codes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a locality based approach for coded computation")
  Member "quasi cyclic flexible regenerating codes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "information theoretically secure erasure codes for distributed storage")
  Member "locally repairable codes with multiple repair alternatives":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "array codes for functional pir and batch codes")
  Member "codes with local regeneration":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "locally recoverable j affine variety codes")
  Member "optimal linear codes with a local error correction property":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on optimal locally repairable codes and generalized sector disk codes")
  Member "locally repairable codes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a locality based approach for coded computation")
  Member "self repairing codes for distributed storage a projective geometric construction":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "functional repair codes a view from projective geometry")
  Member "on the locality of codeword symbols":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a locality based approach for coded computation")

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)