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: "minimum age of information in the internet of things with non uniform status packet sizes"
  Abstract: In this paper, a real-time Internet of Things (IoT) monitoring system is considered in which the IoT devices are scheduled to sample underlying physical processes and send the status updates to a common destination. In a real-world IoT, due to the possibly different dynamics of each physical process, the sizes of the status updates for different devices are often different and each status update typically requires multiple transmission slots. By taking into account such multi-time slot transmissions with non-uniform sizes of the status updates under noisy channels, the problem of joint device scheduling and status sampling is studied in order to minimize the average age of information (AoI) at the destination. This stochastic problem is formulated as an infinite horizon average cost Markov decision process (MDP). The monotonicity of the value function of the MDP is characterized and then used to show that the optimal scheduling and sampling policy is threshold-based with respect to the AoI at each device. To overcome the curse of dimensionality, a low-complexity suboptimal policy is proposed through a semi-randomized base policy and linear approximated value functions. The proposed suboptimal policy is shown to exhibit a similar structure to the optimal policy, which provides a structural base for its effective performance. A structure-aware algorithm is then developed to obtain the suboptimal policy. The analytical results are further extended to the IoT monitoring system with random status update arrivals, for which, the optimal scheduling and sampling policy is also shown to be threshold-based with the AoI at each device. Simulation results illustrate the structures of the optimal policy and show a near-optimal AoI performance resulting from the proposed suboptimal solution approach.

Connected through hyperedge HE-1 (induced by source paper "on the optimality of the whittle s index policy for minimizing the age of information"):
  with members:
    - "age of information with prioritized streams when to buffer preempted packets"
    - "minimizing the age of information noma or oma"
    - "waiting before serving a companion to packet management in status update systems"
    - "whittle index policy for multichannel scheduling in queueing systems"
    - "timely distributed computation with stragglers"
    - "the age of incorrect information a new performance metric for status updates"
    - "a whittle index approach to minimizing functions of age of information"
    - "minimizing the age of information in a csma environment"

Connected through hyperedge HE-2 (induced by source paper "information freshness for timely detection of status changes"):
  with members:
    - "optimal information updating based on value of information"
    - "the age of incorrect information a new performance metric for status updates"
    - "adaptive coding for information freshness in a two user broadcast erasure channel"
    - "information aging through queues a mutual information perspective"
    - "coded status updates in an energy harvesting erasure channel"
    - "age of information minimization for an energy harvesting source with updating erasures with and without feedback"
    - "when to preempt age of information minimization under link capacity constraint"
    - "timely lossless source coding for randomly arriving symbols"

Connected through hyperedge HE-3 (induced by source paper "status updates with priorities lexicographic optimality"):
  with members:
    - "on the optimality of the whittle s index policy for minimizing the age of information"
    - "age of information with prioritized streams when to buffer preempted packets"
    - "minimizing the age of information noma or oma"
    - "waiting before serving a companion to packet management in status update systems"
    - "timely distributed computation with stragglers"
    - "the age of incorrect information a new performance metric for status updates"
    - "minimizing the age of information in a csma environment"
    - "towards assigning priorities in queues using age of information"

Connected through hyperedge HE-4 (induced by source paper "aoi delay tradeoff in mobile edge caching with freshness aware content refreshing"):
  with members:
    - "cooperative service caching and workload scheduling in mobile edge computing"
    - "ai assisted low information latency wireless networking"
    - "age of information aware radio resource management in vehicular networks a proactive deep reinforcement learning perspective"
    - "content popularity prediction towards location aware mobile edge caching"
    - "air ground integrated vehicular network slicing with content pushing and caching"
    - "cost effective cache deployment in mobile heterogeneous networks"
    - "edge caching wireless networks performance analysis and optimization"
    - "edge caching in dense heterogeneous cellular networks with massive mimo aided self backhaul"

Connected through hyperedge HE-5 (induced by source paper "risk aware optimization of age of information in the internet of things"):
  with members:
    - "optimized age of information tail for ultra reliable low latency communications in vehicular networks"
    - "a reinforcement learning framework for optimizing age of information in rf powered communication systems"
    - "taming the tail of maximal information age in wireless industrial networks"
    - "a vision of 6g wireless systems applications trends technologies and open research problems"
    - "reliable transmission of short packets through queues and noisy channels under latency and peak age violation guarantees"
    - "joint status sampling and updating for minimizing age of information in the internet of things"
    - "age of information minimization for an energy harvesting source with updating erasures with and without feedback"
    - "when to preempt age of information minimization under link capacity constraint"

Connected through hyperedge HE-6 (induced by source paper "on the age of information for multicast transmission with hard deadlines in iot systems"):
  with members:
    - "scheduling policies for minimizing age of information in broadcast wireless networks"
    - "joint status sampling and updating for minimizing age of information in the internet of things"
    - "multicast with prioritized delivery how fresh is your data"
    - "status updates through multicast networks"
    - "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)