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 computation in dynamic networks via random walks"
  Abstract: The paper investigates efficient distributed computation in dynamic networks in which the network topology changes (arbitrarily) from round to round. #R##N#Our first contribution is a rigorous framework for design and analysis of distributed random walk algorithms in dynamic networks. We then develop a fast distributed random walk based algorithm that runs in $\tilde{O}(\sqrt{\tau \Phi})$ rounds (with high probability), where $\tau$ is the dynamic mixing time and $\Phi$ is the dynamic diameter of the network respectively, and returns a sample close to a suitably defined stationary distribution of the dynamic network. We also apply our fast random walk algorithm to devise fast distributed algorithms for two key problems, namely, information dissemination and decentralized computation of spectral properties in a dynamic network. #R##N#Our next contribution is a fast distributed algorithm for the fundamental problem of information dissemination (also called as gossip) in a dynamic network. In gossip, or more generally, $k$-gossip, there are $k$ pieces of information (or tokens) that are initially present in some nodes and the problem is to disseminate the $k$ tokens to all nodes. We present a random-walk based algorithm that runs in $\tilde{O}(\min\{n^{1/3}k^{2/3}(\tau \Phi)^{1/3}, nk\})$ rounds (with high probability). To the best of our knowledge, this is the first $o(nk)$-time fully-distributed token forwarding algorithm that improves over the previous-best $O(nk)$ round distributed algorithm [Kuhn et al., STOC 2010], although in an oblivious adversary model. #R##N#Our final contribution is a simple and fast distributed algorithm for estimating the dynamic mixing time and related spectral properties of the underlying dynamic network.

Connected through hyperedge HE-1 (induced by source paper "information spreading in dynamic networks under oblivious adversaries"):
  with members:
    - "storage and search in dynamic peer to peer networks"
    - "lower bounds on information dissemination in dynamic networks"
    - "faster information dissemination in dynamic networks via network coding"
    - "time varying graphs and dynamic networks"
    - "analyzing network coding gossip made easy"
    - "the impact of mobility on gossip algorithms"

Connected through hyperedge HE-2 (induced by source paper "smoothed analysis of dynamic networks"):
  with members:
    - "lower bounds for structuring unreliable radio networks"
    - "information spreading in dynamic graphs"
    - "faster information dissemination in dynamic networks via network coding"
    - "smoothed analysis of algorithms why the simplex algorithm usually takes polynomial time"

Connected through hyperedge HE-3 (induced by source paper "distributed random walks"):
  with members:
    - "near optimal random walk sampling in distributed networks"
    - "distributed verification and hardness of distributed approximation"
    - "faster generation of random spanning trees"
    - "efficient distributed random walks with applications"
    - "expanders via random spanning trees"
    - "lower bounds for distributed markov chain problems"
    - "search in power law networks"

Connected through hyperedge HE-4 (induced by source paper "storage and search in dynamic peer to peer networks"):
  with members:
    - "stochastic analysis of a churn tolerant structured peer to peer scheme"
    - "time varying graphs and dynamic networks"
    - "the effect of faults on network expansion"

Connected through hyperedge HE-5 (induced by source paper "discovery through gossip"):
  with members:
    - "storage and search in dynamic peer to peer networks"
    - "information spreading in dynamic graphs"
    - "quasirandom rumor spreading"
    - "optimal gossip based aggregate computation"

Connected through hyperedge HE-6 (induced by source paper "distributed agreement in dynamic peer to peer networks"):
  with members:
    - "dex self healing expanders"
    - "xheal localized self healing using expanders"
    - "information spreading in dynamic graphs"
    - "faster information dissemination in dynamic networks via network coding"
    - "time varying graphs and dynamic networks"
    - "breaking the o n 2 bit barrier scalable byzantine agreement with an adaptive adversary"
    - "the effect of faults on network expansion"
    - "fast distributed algorithms for computing separable functions"

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)