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: "an asymptotically efficient backlog estimate for dynamic frame aloha"
  Abstract: In this paper we investigate backlog estimation procedures for Dynamic Frame Aloha (DFA) in Radio Frequency Identification (RFID) environment. In particular, we address the tag identification efficiency with any tag number $N$, including $N\rightarrow\infty$. Although in the latter case efficiency $e^{-1}$ is possible, none of the solution proposed in the literature has been shown to reach such value. We analyze Schoute's backlog estimate, which is very attractive for its simplicity, and formally show that its asymptotic efficiency is 0.311. Leveraging the analysis, we propose the Asymptotic Efficient backlog Estimate (AE$^2$) an improvement of the Schoute's backlog estimate, whose efficiency reaches $e^{-1}$ asymptotically. We further show that AE$^2$ can be optimized in order to present an efficiency very close to $e^{-1}$ for practically any value of the population size. We also evaluate the loss of efficiency when the frame size is constrained to be a power of two, as required by RFID standards for DFA, and theoretically show that the asymptotic efficiency becomes 0.356.

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.IT(Information Theory)