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: "fountain codes based distributed storage algorithms for large scale wireless sensor networks"
  Abstract: We consider large-scale networks with n nodes, out of which k are in possession, (e.g., have sensed or collected in some other way) k information packets. In the scenarios in which network nodes are vulnerable because of, for example, limited energy or a hostile environment, it is desirable to disseminate the acquired information throughout the network so that each of the n nodes stores one (possibly coded) packet and the original k source packets can be recovered later in a computationally simple way from any (1 + \varepsilon)k nodes for some small \varepsilon > 0. We developed two distributed algorithms for solving this problem based on simple random walks and Fountain codes. Unlike all previously developed schemes, our solution is truly distributed, that is, nodes do not know n, k or connectivity in the network, except in their own neighborhoods, and they do not maintain any routing tables. In the first algorithm, all the sensors have the knowledge of n and k. In the second algorithm, each sensor estimates these parameters through the random walk dissemination. We present analysis of the communication/transmission and encoding/decoding complexity of these two algorithms, and provide extensive simulation results as well.

Connected through hyperedge HE-1 (induced by source paper "robust node estimation and topology discovery algorithm in large scale wireless sensor networks"):
  with members:
    - "sampling content distributed over graphs"
    - "decentralized coding algorithms for distributed storage in wireless sensor networks"

Connected through hyperedge HE-2 (induced by source paper "distributed storage allocations"):
  with members:
    - "symmetric allocations for distributed storage"
    - "memory allocation in distributed storage networks"

Connected through hyperedge HE-3 (induced by source paper "distributed data collection and storage algorithms for collaborative learning vision sensor devices with applications to pilgrimage"):
  with members:
    - "a distributed data collection algorithm for wireless sensor networks with persistent storage nodes"
    - "decentralized coding algorithms for distributed storage in wireless sensor networks"
    - "network coding for distributed storage systems"
    - "decentralized erasure codes for distributed networked storage"

Connected through hyperedge HE-4 (induced by source paper "distributed storage allocations for optimal delay"):
  with members:
    - "symmetric allocations for distributed storage"

Connected through hyperedge HE-5 (induced by source paper "a distributed data collection algorithm for wireless sensor networks with persistent storage nodes"):
  with members:
    - "decentralized coding algorithms for distributed storage in wireless sensor networks"
    - "raptor codes based distributed storage algorithms for wireless sensor networks"
    - "decentralized erasure codes for distributed networked storage"

Connected through hyperedge HE-6 (induced by source paper "multiresolution cube estimators for sensor network aggregate queries"):
  with members:
    - "decentralized erasure codes for distributed networked storage"

Connected through hyperedge HE-7 (induced by source paper "distributed flooding based storage algorithms for large scale sensor networks"):
  with members:
    - "raptor codes based distributed storage algorithms for wireless sensor networks"

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)