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: "fault tolerant aggregation flow updating meets mass distribution"
  Abstract: Flow-Updating (FU) is a fault-tolerant technique that has proved to be efficient in practice for the distributed computation of aggregate functions in communication networks where individual processors do not have access to global information. Previous distributed aggregation protocols, based on repeated sharing of input values (or mass) among processors, sometimes called Mass-Distribution (MD) protocols, are not resilient to communication failures (or message loss) because such failures yield a loss of mass.#R##N##R##N#In this paper, we present a protocol which we call Mass-Distribution with Flow-Updating (MDFU). We obtain MDFU by applying FU techniques to classic MD. We analyze the convergence time of MDFU showing that stochastic message loss produces low overhead. This is the first convergence proof of an FU-based algorithm. We evaluate MDFU experimentally, comparing it with previous MD and FU protocols, and verifying the behavior predicted by the analysis. Finally, given that MDFU incurs a fixed deviation proportional to the message-loss rate, we adjust the accuracy of MDFU heuristically in a new protocol called MDFU with Linear Prediction (MDFU-LP). The evaluation shows that both MDFU and MDFU-LP behave very well in practice, even under high rates of message loss and even changing the input values dynamically.

Connected through hyperedge HE-1 (induced by source paper "counting in practical anonymous dynamic networks is polynomial"):
  with members:
    - "a faster counting protocol for anonymous dynamic networks"
    - "naming and counting in anonymous unknown dynamic networks"

Connected through hyperedge HE-2 (induced by source paper "a faster counting protocol for anonymous dynamic networks"):
  with members:
    - "counting in practical anonymous dynamic networks is polynomial"
    - "investigating the cost of anonymity on dynamic networks"
    - "naming and counting in anonymous unknown dynamic networks"
    - "time varying graphs and dynamic networks"

Connected through hyperedge HE-3 (induced by source paper "spectra robust estimation of distribution functions in networks"):
  with members:
    - "a survey of distributed data aggregation algorithms"
    - "dependability in aggregation by averaging"
    - "medians and beyond new aggregation techniques for sensor networks"

Connected through hyperedge HE-4 (induced by source paper "a survey of distributed data aggregation algorithms"):
  with members:
    - "spectra robust estimation of distribution functions in networks"
    - "dependability in aggregation by averaging"
    - "a survey of green networking research"
    - "geographic gossip efficient averaging for sensor networks"
    - "dynamic approaches to in network aggregation"
    - "geographic gossip efficient aggregation for sensor networks"
    - "fast distributed algorithms for computing separable functions"
    - "medians and beyond new aggregation techniques for 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.DC(Distributed, Parallel, and Cluster Computing)