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: "failure based lifespan performance analysis of network fabric in modular data centers toward deployment in canada s north"
  Abstract: Data centers have evolved from a passive element of compute infrastructure to become an active and core part of any ICT solution. Modular data centers are a promising design approach to improve resiliency of data centers, and they can play a key role in deploying ICT infrastructure in remote and in- hospitable environments with low temperatures and hydro- and wind-electric capabilities. Modular data centers can also survive even with lack of contin- uous physical maintenance and support. Generally, the most critical part of a data center is its network fabric that could impede the whole system even if all other components are fully functional. In this work, a complete failure analysis of modular data centers using failure models of various components including servers, switches, and links is performed using a proposed Monte- Carlo approach. This approach allows us to calculate the performance of a design along its lifespan even at the terminal stages. A class of modified

Connected through hyperedge HE-1 (induced by source paper "dynamic bandwidth efficient bcube topologies for virtualized data center networks"):
  with members:
    - "a monte carlo approach to lifespan failure performance analysis of the network fabric in modular data centers"
    - "performance comparison of link node and zone disjoint multi path routing strategies and minimum hop single path routing for mobile ad hoc 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.PF(Performance)