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: "context aware information lapse for timely status updates in remote control systems"
  Abstract: Emerging applications in Internet of Things (IoT), such as remote monitoring and control, extensively rely on timely status updates. Age of Information (AoI) has been proposed to characterize the freshness of information in status update systems. However, it only considers the time elapsed since the generation of the latest packet, and is incapable of capturing other critical information in remote control systems, such as the stochastic evolution and the importance of the source status. In order to evaluate the timeliness of status updates in remote control systems, we propose a context-aware metric, namely the context-aware information lapse. The context-aware information lapse characterizes both the stochastic evolution of the source status and the context-aware importance of the status. In this paper, the minimization of average context-aware lapse in a multi-user system is considered, and a corresponding user scheduling policy is proposed based on Lyapunov optimization. Numerical results show that compared to AoI-based policy, the context-aware-lapse-based policy can achieve a substantial improvement in terms of error-threshold violation probability and control performance.

Connected through hyperedge HE-1 (induced by source paper "urgency of information for context aware timely status updates in remote control systems"):
  with members:
    - "a general formula for the stationary distribution of the age of information and its application to single server queues"
    - "sampling for remote estimation through queues age of information and beyond"
    - "the age of incorrect information a new performance metric for status updates"
    - "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"
    - "sampling for data freshness optimization non linear age functions"
    - "age of information in g g 1 1 systems"
    - "stochastic control with stale information part i fully observable systems"

Connected through hyperedge HE-2 (induced by source paper "beyond age urgency of information for timeliness guarantee in status update systems"):
  with members:
    - "sampling for remote estimation through queues age of information and beyond"
    - "the age of incorrect information a new performance metric for status updates"
    - "scheduling policies for minimizing age of information in broadcast wireless networks"
    - "stochastic control with stale information part i fully observable systems"
    - "wireless network design for control systems a survey"
    - "remote estimation of the wiener process over a channel with random delay"
    - "update or wait how to keep your data fresh"
    - "context aware computing for the internet of things a survey"

Connected through hyperedge HE-3 (induced by source paper "timely distributed computation with stragglers"):
  with members:
    - "straggler mitigation at scale"
    - "trading off computation with transmission in status update systems"
    - "age of information with prioritized streams when to buffer preempted packets"
    - "sampling for remote estimation through queues age of information and beyond"
    - "computation scheduling for distributed machine learning with straggling workers"
    - "age of information for computation intensive messages in mobile edge computing"
    - "age of information for discrete time queues"
    - "on timely channel coding with hybrid arq"

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)