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: "fast distributed algorithms for computing separable functions"
  Abstract: The problem of computing functions of values at the nodes in a network in a totally distributed manner, where nodes do not have unique identities and make decisions based only on local information, has applications in sensor, peer-to-peer, and ad-hoc networks. The task of computing separable functions, which can be written as linear combinations of functions of individual variables, is studied in this context. Known iterative algorithms for averaging can be used to compute the normalized values of such functions, but these algorithms do not extend in general to the computation of the actual values of separable functions. #R##N#The main contribution of this paper is the design of a distributed randomized algorithm for computing separable functions. The running time of the algorithm is shown to depend on the running time of a minimum computation algorithm used as a subroutine. Using a randomized gossip mechanism for minimum computation as the subroutine yields a complete totally distributed algorithm for computing separable functions. For a class of graphs with small spectral gap, such as grid graphs, the time used by the algorithm to compute averages is of a smaller order than the time required by a known iterative averaging scheme.

Connected through hyperedge HE-1 (induced by source paper "distributed voting in beep model"):
  with members:
    - "distributed voting ranking with optimal number of states per node"
    - "beeping a maximal independent set fast"
    - "deterministic rendezvous with detection using beeps"
    - "counting in one hop beeping networks"
    - "naming a channel with beeps"
    - "asynchronous broadcasting with bivalent beeps"
    - "feedback from nature simple randomised distributed algorithms for maximal independent set selection and greedy colouring"
    - "design patterns in beeping algorithms examples emulation and analysis"

Connected through hyperedge HE-2 (induced by source paper "token based function computation with memory"):
  with members:
    - "coalescing random walks and voting on connected graphs"
    - "gossip algorithms for distributed signal processing"

Connected through hyperedge HE-3 (induced by source paper "finite time convergent gossiping"):
  with members:
    - "consensus over random graph processes network borel cantelli lemmas for almost sure convergence"
    - "finite time consensus using stochastic matrices with positive diagonals"
    - "the evolution of beliefs over signed social networks"
    - "analysis of sum weight like algorithms for averaging in wireless sensor networks"
    - "opinion fluctuations and disagreement in social networks"
    - "convergence rate analysis of distributed gossip linear parameter estimation fundamental limits and tradeoffs"
    - "gossip algorithms for distributed signal processing"
    - "order optimal consensus through randomized path averaging"

Connected through hyperedge HE-4 (induced by source paper "a generalized bass model for product growth in networks"):
  with members:
    - "epidemic spreading with external agents"
    - "optimal pricing in networks with externalities"

Connected through hyperedge HE-5 (induced by source paper "rumor spreading with bounded in degree"):
  with members:
    - "on the push pull protocol for rumour spreading"
    - "tight bounds for rumor spreading with vertex expansion"
    - "simple fast and deterministic gossip and rumor spreading"
    - "global computation in a poorly connected world fast rumor spreading with no dependence on conductance"
    - "optimal gossip based aggregate computation"

Connected through hyperedge HE-6 (induced by source paper "consensus over random graph processes network borel cantelli lemmas for almost sure convergence"):
  with members:
    - "finite time convergent gossiping"
    - "distributed averaging via lifted markov chains"
    - "distributed sensor localization in random environments using minimal number of anchor nodes"
    - "distributed consensus algorithms in sensor networks quantized data and random link failures"

Connected through hyperedge HE-7 (induced by source paper "gossip vs markov chains and randomness efficient rumor spreading"):
  with members:
    - "rumor spreading in random evolving graphs"
    - "tight bounds for rumor spreading with vertex expansion"
    - "quasirandom load balancing"
    - "tight bounds for randomized load balancing on arbitrary network topologies"
    - "simple fast and deterministic gossip and rumor spreading"
    - "better pseudorandom generators from milder pseudorandom restrictions"
    - "global computation in a poorly connected world fast rumor spreading with no dependence on conductance"
    - "space efficient local computation algorithms"

Connected through hyperedge HE-8 (induced by source paper "on the role of mobility for multimessage gossip"):
  with members:
    - "information spreading in dynamic graphs"
    - "tight bounds on information dissemination in sparse mobile networks"
    - "information spreading in stationary markovian evolving graphs"
    - "analyzing network coding gossip made easy"
    - "distributed averaging via lifted markov chains"
    - "the impact of mobility on gossip algorithms"
    - "gossiping with multiple messages"

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.NI(Networking and Internet Architecture)