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: "measuring and understanding throughput of network topologies"
  Abstract: High throughput is of particular interest in data center and HPC networks. Although myriad network topologies have been proposed, a broad head-to-head comparison across topologies and across traffic patterns is absent, and the right way to compare worst-case throughput performance is a subtle problem. #R##N#In this paper, we develop a framework to benchmark the throughput of network topologies, using a two-pronged approach. First, we study performance on a variety of synthetic and experimentally-measured traffic matrices (TMs). Second, we show how to measure worst-case throughput by generating a near-worst-case TM for any given topology. We apply the framework to study the performance of these TMs in a wide range of network topologies, revealing insights into the performance of topologies with scaling, robustness of performance across TMs, and the effect of scattered workload placement. Our evaluation code is freely available.

Connected through hyperedge HE-1 (induced by source paper "metteor robust multi traffic topology engineering for commercial data center networks"):
  with members:
    - "expanding across time to deliver bandwidth efficiency and low latency"
    - "space shuffle a scalable flexible and high performance data center network"
    - "jellyfish networking data centers randomly"

Connected through hyperedge HE-2 (induced by source paper "fatpaths routing in supercomputers data centers and clouds with low diameter networks when shortest paths fall short"):
  with members:
    - "slim fly a cost effective low diameter network topology"
    - "expander datacenters from theory to practice"
    - "homa a receiver driven low latency transport protocol using network priorities"
    - "revisiting network support for rdma"
    - "a survey and evaluation of data center network topologies"
    - "enabling highly scalable remote memory access programming with mpi 3 one sided"
    - "jellyfish networking data centers randomly"

Connected through hyperedge HE-3 (induced by source paper "expander datacenters from theory to practice"):
  with members:
    - "optimal networks from error correcting codes"
    - "high throughput data center topology design"

Connected through hyperedge HE-4 (induced by source paper "on hash based work distribution methods for parallel best first search"):
  with members:
    - "a survey of parallel a"
    - "recent advances in graph partitioning"
    - "evaluation of a simple scalable parallel best first search strategy"
    - "the fast downward planning system"

Connected through hyperedge HE-5 (induced by source paper "high throughput data center topology design"):
  with members:
    - "jellyfish networking data centers randomly"

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)