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: "age of information aware cache updating with file and age dependent update durations"
  Abstract: We consider a system consisting of a library of time-varying files, a server that at all times observes the current version of all files, and a cache that at the beginning stores the current versions of all files but afterwards has to update %fresh versions of these files from the server. Unlike previous works, the update duration is not constant but depends on the file and its Age of Information (AoI), i.e., of the time elapsed since it was last updated. The goal of this work is to design an update policy that minimizes the average AoI of all files with respect to a given popularity distribution. Actually a relaxed problem, close to the original optimization problem, is solved and a practical update policy is derived. The update policy relies on the file popularity and on the functions that characterize the update durations of the files depending on their AoI. Numerical simulations show a significant improvement of this new update policy compared to the so-called square-root policy that is optimal under file-independent and constant update durations.

Connected through hyperedge HE-1 (induced by source paper "who should google scholar update more often"):
  with members:
    - "optimal selective encoding for timely updates"
    - "trading off computation with transmission in status update systems"
    - "average peak age of information minimization in uav assisted iot networks"
    - "a reinforcement learning framework for optimizing age of information in rf powered communication systems"
    - "reducing age of information for computation intensive messages via packet replacement"
    - "timely distributed computation with stragglers"
    - "age of information in multicast networks with multiple update streams"
    - "age of information for updates with distortion constant and age dependent distortion constraints"

Connected through hyperedge HE-2 (induced by source paper "aoi and energy consumption oriented dynamic status updating in caching enabled iot networks"):
  with members:
    - "optimizing information freshness in computing enabled iot networks"
    - "dynamic content update for wireless edge caching via deep reinforcement learning"

Connected through hyperedge HE-3 (induced by source paper "age of information for updates with distortion constant and age dependent distortion constraints"):
  with members:
    - "age of information for computation intensive messages in mobile edge computing"
    - "timely distributed computation with stragglers"
    - "age of information for updates with distortion"
    - "towards the tradeoff between service performance and information freshness"
    - "age of information with finite horizon and partial updates"
    - "online timely status updates with erasures for energy harvesting sensors"
    - "minimizing age of information with soft updates"
    - "optimal status updating for an energy harvesting sensor with a noisy channel"

Connected through hyperedge HE-4 (induced by source paper "accounting for information freshness in scheduling of content caching"):
  with members:
    - "dynamic content updates in heterogeneous wireless networks"
    - "on optimal proactive and retention aware caching with user mobility"
    - "using grouped linear prediction and accelerated reinforcement learning for online content caching"
    - "caching with time varying popularity profiles a learning theoretic perspective"
    - "optimal geographic caching in cellular networks with linear content coding"
    - "cost optimal caching for d2d networks with user mobility modeling analysis and computational approaches"
    - "update or wait how to keep your data fresh"
    - "capacity of cellular networks with femtocache"

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)