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: "locally adaptive scheduling policy for optimizing information freshness in wireless networks"
  Abstract: Optimization of information freshness in wireless networks has usually been performed based on queueing analysis that captures only the temporal traffic dynamics associated with the transmitters and receivers. However, the effect of interference, which is mainly dominated by the interferers' geographic locations, is not well understood. In this paper, we leverage a spatiotemporal model, which allows one to characterize the age of information (AoI) from a joint queueing-geometry perspective, and design a decentralized scheduling policy that exploits local observation to make transmission decisions that minimize the AoI. Simulations results reveal that the proposed scheme not just largely reduces the peak AoI but also scales well with the network size.

Connected through hyperedge HE-1 (induced by source paper "a spatiotemporal framework for information freshness in iot uplink networks"):
  with members:
    - "age of information in poisson networks"
    - "average age of information with hybrid arq under a resource constraint"
    - "modeling and analysis of cellular networks using stochastic geometry a tutorial"
    - "the meta distribution of the sir for cellular networks with power control"
    - "heterogeneous cellular networks with spatio temporal traffic delay analysis and scheduling"
    - "the age of information real time status updating by multiple sources"
    - "the meta distribution of the sir in poisson bipolar and cellular networks"
    - "on stochastic geometry modeling of cellular uplink transmission with truncated channel inversion power control"

Connected through hyperedge HE-2 (induced by source paper "a spatiotemporal model for peak aoi in uplink iot networks time vs event triggered traffic"):
  with members:
    - "a spatiotemporal framework for information freshness in iot uplink networks"
    - "optimizing information freshness in computing enabled iot networks"
    - "can determinacy minimize age of information"
    - "age of information in poisson networks"
    - "average age of information with hybrid arq under a resource constraint"
    - "modeling and analysis of cellular networks using stochastic geometry a tutorial"
    - "the meta distribution of the sir for cellular networks with power control"
    - "analytical modeling of interference aware power control for the uplink of heterogeneous cellular networks"

Connected through hyperedge HE-3 (induced by source paper "edge caching with real time guarantees"):
  with members:
    - "age of information performance of multiaccess strategies with packet management"
    - "optimizing information freshness in wireless networks under general interference constraints"
    - "optimizing age of information in wireless networks with perfect channel state information"
    - "age of information in poisson networks"
    - "analysis and optimization of caching and multicasting in large scale cache enabled wireless networks"
    - "heterogeneous cellular networks with flexible cell association a comprehensive downlink sinr analysis"

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)