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: "a spatiotemporal framework for information freshness in iot uplink networks"
  Abstract: Timely message delivery is a key enabler for Internet of Things (IoT) and cyber-physical systems to support wide range of context-dependent applications. Conventional time-related metrics, such as delay, fails to characterize the timeliness of the system update or to capture the freshness of information from application perspective. Age of information (AoI) is a time.evolving measure of information freshness that has received considerable attention during the past years. In the foreseen large scale and dense IoT networks, joint temporal (i.e., queue aware) and spatial (i.e., mutual interference aware) characterization of the AoI is required. In this work we provide a spatiotemporal framework that captures the peak AoI for large scale IoT uplink network. To this end, the paper quantifies the peak AoI for large scale cellular network with Bernoulli uplink traffic. Simulation results are conducted to validate the proposed model and show the effect of traffic load and decoding threshold. Insights are driven to characterize the network stability frontiers and the location-dependent performance within the network.

Connected through hyperedge HE-1 (induced by source paper "a spatiotemporal model for peak aoi in uplink iot networks time vs event triggered traffic"):
  with members:
    - "optimizing information freshness in computing enabled iot networks"
    - "locally adaptive scheduling policy for optimizing information freshness in wireless 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"

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)