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: "minimizing the age of information from sensors with common observations"
  Abstract: We study the average Age of Information (AoI) in a system where physical sources produce independent discrete-time updates that are each observed by several sensors. We devise a model that is simple, but still capable to capture the main tradeoffs. Two sensor scheduling policies are proposed to minimize the AoI of the sources; one in which the system parameters are assumed known, and one in which they are learned. Both policies are able to exploit the common sensor information to reduce the AoI, resulting in large reductions in AoI compared to common schedules.

Connected through hyperedge HE-1 (induced by source paper "on the age of information in internet of things systems with correlated devices"):
  with members:
    - "age of information analysis for dynamic spectrum sharing"
    - "minimizing the age of information of cognitive radio based iot systems under a collision constraint"
    - "sampling for remote estimation through queues age of information and beyond"
    - "a reinforcement learning framework for optimizing age of information in rf powered communication systems"
    - "age of information in multiple sensing of a single source"
    - "status from a random field how densely should one update"
    - "age of information in multiple sensing"
    - "minimizing the age of information in a csma environment"

Connected through hyperedge HE-2 (induced by source paper "active status update packet drop control in an energy harvesting node"):
  with members:
    - "using erasure feedback for online timely updating with an energy harvesting sensor"
    - "online timely status updates with erasures for energy harvesting sensors"
    - "age of information performance of multiaccess strategies with packet management"
    - "the age of updates in a simple relay network"
    - "age of information minimization for an energy harvesting source with updating erasures with and without feedback"
    - "joint information freshness and completion time optimization for vehicular networks"
    - "scheduling status updates to minimize age of information with an energy harvesting sensor"
    - "optimal status update for age of information minimization with an energy harvesting source"

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)