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: "narses a scalable flow based network simulator"
  Abstract: Most popular, modern network simulators, such as ns, are targeted towards simulating low-level protocol details. These existing simulators are not intended for simulating large distributed applications with many hosts and many concurrent connections over long periods of simulated time. We introduce a new simulator, Narses, targeted towards large distributed applications. The goal of Narses is to simulate and validate large applications efficiently using network models of varying levels of detail. We introduce several simplifying assumptions that allow our simulator to scale to the needs of large distributed applications while maintaining a reasonable degree of accuracy. Initial results show up to a 45 times speedup while consuming 28% of the memory used by ns. Narses maintains a reasonable degree of accuracy -- within 8% on average.

Connected through hyperedge HE-1 (induced by source paper "attrition defenses for a peer to peer digital preservation system"):
  with members:
    - "active internet traffic filtering real time response to denial of service attacks"
    - "preserving peer replicas by rate limited sampled voting"

Connected through hyperedge HE-2 (induced by source paper "practical load balancing for content requests in peer to peer networks"):
  with members:
    - "cup controlled update propagation in peer to peer networks"
    - "enabling the long term archival of signed documents through time stamping"

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.PF(Performance)