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: "on the maximum rate of networked computation in a capacitated network"
  Abstract: Given a capacitated communication network $\mathcal{N}$ and a function f that needs to be computed on $\mathcal{N},$ we study the problem of generating a computation and communication schedule in $\mathcal{N}$ to maximize the rate of computation of f. Shah et. al.[IEEE Journal of Selected Areas in Communication, 2013] studied this problem when the computation schema $\mathcal{G}$ for f is a tree. We define the notion of a schedule when $\mathcal{G}$ is a general DAG and show that finding an optimal schedule is equivalent to finding the solution of a packing LP. We prove that approximating the maximum rate is MAX SNP-hard by looking at the packing LP. For this packing LP we prove that solving the separation oracle of its dual is equivalent to solving the LP. The separation oracle of the dual reduces to the problem of finding minimum cost embedding given $\mathcal{N},\mathcal{G},$ which we prove to be MAX SNP-hard even when $\mathcal{G}$ has bounded degree and bounded edge weights and $\mathcal{N}$ has just three vertices. We present a polynomial time algorithm to compute the maximum rate of function computation when $\mathcal{N}$ has two vertices by reducing the problem to a version of submodular function minimization problem. For the general $\mathcal{N}$ we study restricted class of schedules and its equivalent packing LP. We observe that for this packing LP also the separation oracle of its dual reduces to finding minimum cost embedding. A version of this minimum cost embedding problem has been studied in literature. We present a quadratic integer program for the minimum cost embedding problem and its linear programming relaxation based on earthmover metric. We also present some approximate algorithms for special classes of $\mathcal{G}.$

Connected through hyperedge HE-1 (induced by source paper "random walk based in network computation of arbitrary functions"):
  with members:
    - "decentralized random walk based data collection in networks"
    - "on coalescence time in graphs when is coalescing as fast as meeting"
    - "optimal embedding of functions for in network computation complexity analysis and algorithms"
    - "coalescing random walks and voting on connected graphs"
    - "tight bounds for randomized load balancing on arbitrary network topologies"
    - "towards a queueing based framework for in network function computation"

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)