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: "towards a system theoretic approach to wireless network capacity in finite time and space"
  Abstract: In asymptotic regimes, both in time and space (network size), the derivation of network capacity results is grossly simplified by brushing aside queueing behavior in non-Jackson networks. This simplifying double-limit model, however, lends itself to conservative numerical results in finite regimes. To properly account for queueing behavior beyond a simple calculus based on average rates, we advocate a system theoretic methodology for the capacity problem in finite time and space regimes. This methodology also accounts for spatial correlations arising in networks with CSMA/CA scheduling and it delivers rigorous closed-form capacity results in terms of probability distributions. Unlike numerous existing asymptotic results, subject to anecdotal practical concerns, our transient one can be used in practical settings: for example, to compute the time scales at which multi-hop routing is more advantageous than single-hop routing.

Connected through hyperedge HE-1 (induced by source paper "on the reliability of lte random access performance bounds for machine to machine burst resolution time"):
  with members:
    - "ultra reliable communication in 5g wireless systems"
    - "an end to end probabilistic network calculus with moment generating functions"

Connected through hyperedge HE-2 (induced by source paper "bound based power optimization for multi hop heterogeneous wireless industrial networks under statistical delay constraints"):
  with members:
    - "statistical delay bound for wirelesshart networks"
    - "non equilibrium information envelopes and the capacity delay error tradeoff of source coding"
    - "delay constrained throughput analysis of a correlated mimo wireless channel"
    - "energy efficient scheduling of delay constrained traffic over fading channels"
    - "an end to end probabilistic network calculus with moment generating functions"

Connected through hyperedge HE-3 (induced by source paper "power minimization under statistical delay constraints for multi hop wireless industrial networks"):
  with members:
    - "statistical delay bound for wirelesshart networks"
    - "non equilibrium information envelopes and the capacity delay error tradeoff of source coding"
    - "delay constrained throughput analysis of a correlated mimo wireless channel"
    - "an end to end probabilistic network calculus with moment generating functions"

Connected through hyperedge HE-4 (induced by source paper "on the catalyzing effect of randomness on the per flow throughput in wireless networks"):
  with members:
    - "capacity of large scale csma wireless networks"
    - "rethinking information theory for mobile ad hoc networks"
    - "an end to end probabilistic network calculus with moment generating 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.PF(Performance)