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: "real time remote estimation with hybrid arq in wireless networked control"
  Abstract: Real-time remote estimation is critical for mission-critical applications including industrial automation, smart grid and tactile Internet. In this paper, we propose a hybrid automatic repeat request (HARQ)-based real-time remote estimation framework for linear time-invariant (LTI) dynamic systems. Considering the estimation quality of such a system, there is a fundamental tradeoff between the reliability and freshness of the sensor's measurement transmission. We formulate a new problem to optimize the sensor's online transmission control policy for static and Markov fading channels, which depends on both the current estimation quality of the remote estimator and the current number of retransmissions of the sensor, so as to minimize the long-term remote estimation mean squared error (MSE). This problem is non-trivial. In particular, it is challenging to derive the condition in terms of the communication channel quality and the LTI system parameters, to ensure a bounded long-term estimation MSE. We derive an elegant sufficient condition of the existence of a stationary and deterministic optimal policy that stabilizes the remote estimation system and minimizes the MSE. Also, we prove that the optimal policy has a switching structure, and accordingly derive a low-complexity suboptimal policy. Numerical results show that the proposed optimal policy significantly improves the performance of the remote estimation system compared to the conventional non-HARQ policy.

Connected through hyperedge HE-1 (induced by source paper "recursive optimization of finite blocklength allocation to mitigate age of information outage"):
  with members:
    - "secure short packet communications for mission critical iot applications"
    - "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"
    - "julia a fresh approach to numerical computing"
    - "policy iteration for factored mdps"

Connected through hyperedge HE-2 (induced by source paper "optimal downlink uplink scheduling of wireless networked control for industrial iot"):
  with members:
    - "to retransmit or not real time remote estimation in wireless networked control"
    - "wireless network design for control systems a survey"
    - "why to decouple the uplink and downlink in cellular networks and how to do it"
    - "the emerging internet of things marketplace from an industrial perspective a survey"
    - "on the complexity of solving markov decision problems"
    - "in band full duplex wireless challenges and opportunities"
    - "optimal packet scheduling in an energy harvesting communication system"

Connected through hyperedge HE-3 (induced by source paper "finite blocklength allocation towards robust age of information optimization"):
  with members:
    - "secure short packet communications for mission critical iot applications"
    - "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"
    - "energy latency tradeoff in ultra reliable low latency communication with retransmissions"
    - "wirelessly powered communication networks with short packets"
    - "julia a fresh approach to numerical computing"
    - "policy iteration for factored mdps"

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)