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 of cognitive radio based iot systems under a collision constraint"
  Abstract: This paper considers a cognitive radio-based IoT monitoring system, consisting of an IoT device that aims to update its measurement to a destination using cognitive radio technique. Specifically, the IoT device as a secondary user (SIoT), seeks and exploits the spectrum opportunities of the licensed band vacated by its primary user (PU) to deliver status updates without causing visible effects to the licensed operation. In this context, the SIoT should carefully make use of the licensed band and schedule when to transmit to maintain the timeliness of the status update. We adopt a recent metric, Age of Information (AoI), to characterize the timeliness of the status update of the SIoT. We aim to minimize the long-term average AoI of the SIoT while satisfying the collision constraint imposed by the PU by formulating a constrained Markov decision process (CMDP) problem. We first prove the existence of optimal stationary policy of the CMDP problem. The optimal stationary policy (termed age-optimal policy) is shown to be a randomized simple policy that randomizes between two deterministic policies with a fixed probability. We prove that the two deterministic policies have a threshold structure and further derive the closed-form expression of average AoI and collision probability for the deterministic threshold-structured policy by conducting Markov Chain analysis. The analytical expression offers an efficient way to calculate the threshold and randomization probability to form the age-optimal policy. For comparison, we also consider the throughput maximization policy (termed throughput-optimal policy) and analyze the average AoI performance under the throughput-optimal policy in the considered system. Numerical simulations show the superiority of the derived age-optimal policy over the throughput-optimal policy. We also unveil the impacts of various system parameters on the corresponding optimal policy and the resultant average AoI.

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"
    - "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"
    - "scheduling to minimize age of information in multi state time varying networks with power constraints"

Connected through hyperedge HE-2 (induced by source paper "age of information dependent random access for massive iot networks"):
  with members:
    - "age oriented opportunistic relaying in cooperative status update systems with stochastic arrivals"
    - "minimizing age of information via hybrid noma oma"
    - "minimizing the age of information noma or oma"
    - "minimizing age of information for real time monitoring in resource constrained industrial iot networks"
    - "age of information in random access channels"
    - "scheduling policies for minimizing age of information in broadcast wireless networks"
    - "can decentralized status update achieve universally near optimal age of information in wireless multiaccess channels"
    - "timely status update in massive iot systems decentralized scheduling for wireless uplinks"

Connected through hyperedge HE-3 (induced by source paper "multiuser scheduling for minimizing age of information in uplink mimo systems"):
  with members:
    - "age oriented opportunistic relaying in cooperative status update systems with stochastic arrivals"
    - "minimizing age of information via hybrid noma oma"
    - "on the optimality of the whittle s index policy for minimizing the age of information"
    - "age of information dependent random access for massive iot networks"
    - "minimizing the age of information in wireless networks with stochastic arrivals"
    - "age optimal updates of multiple information flows"
    - "scheduling policies for minimizing age of information in broadcast wireless networks"
    - "a reinforcement learning approach to age of information in multi user networks"

Connected through hyperedge HE-4 (induced by source paper "minimizing age of information via hybrid noma oma"):
  with members:
    - "minimizing the age of information noma or oma"
    - "minimizing the age of information in wireless networks with stochastic arrivals"
    - "minimizing age of information for real time monitoring in resource constrained industrial iot networks"
    - "minimizing the age of information in a csma environment"
    - "scheduling policies for minimizing age of information in broadcast wireless networks"
    - "can decentralized status update achieve universally near optimal age of information in wireless multiaccess channels"
    - "to skip or to switch minimizing age of information under link capacity constraint"
    - "average age of information with hybrid arq under a resource constraint"

Connected through hyperedge HE-5 (induced by source paper "age oriented opportunistic relaying in cooperative status update systems with stochastic arrivals"):
  with members:
    - "timely updates in energy harvesting two hop networks offline and online policies"
    - "minimizing age of information for real time monitoring in resource constrained industrial iot networks"
    - "the age of updates in a simple relay network"
    - "average age of information with hybrid arq under a resource constraint"
    - "update or wait how to keep your data fresh"
    - "on the age of information in status update systems with packet management"

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)