human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "age optimal sampling and transmission scheduling in multi source systems"):
  Abstract: In this paper, we consider the problem of minimizing the age of information in a multi-source system, where sources communicate their update packets to a destination via a channel with random delay. Due to interference, only one source can be scheduled at a time. We consider the problem of finding a decision policy that controls the packet sampling times and schedules source transmissions to minimize the total average peak age (TaPA) and the total average age (TaA) of the sources. Our investigation of this problem results in an important separation principle: The optimal scheduling strategy and the optimal sampling strategy are independent of each other. In particular, we prove that, given the sampling times of the update packets, the Maximum Age First (MAF) scheduling strategy provides the best age performance among all scheduling strategies. This transforms our overall optimization problem into an optimal sampling problem, given that the decision policy follows the MAF scheduling strategy. Interestingly, we show that the zero-wait sampler (in which a packet is generated once the channel is idle) is optimal for minimizing the TaPA, while it does not always minimize the TaA. We use Dynamic Programming (DP) to investigate the optimal sampler for minimizing the TaA. Finally, we provide an approximate analysis of Bellman's equation to approximate the TaA-optimal sampler by a water-filling solution and demonstrate its efficacy through numerical evaluations.

Includes members:
  Member "age optimal updates of multiple information flows":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "timely updates by multiple sources the m m 1 queue revisited")
  Member "scheduling policies for minimizing age of information in broadcast wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "who should google scholar update more often")
  Member "information aging through queues a mutual information perspective":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "who should google scholar update more often")
  Member "sampling for data freshness optimization non linear age functions":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "urgency of information for context aware timely status updates in remote control systems")
  Member "distributed scheduling algorithms for optimizing information freshness in wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "timely updates by multiple sources the m m 1 queue revisited")
  Member "optimizing information freshness in wireless networks under general interference constraints":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "optimizing information freshness in wireless networks a stochastic geometry approach")
  Member "optimizing age of information in wireless networks with perfect channel state information":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "timely updates by multiple sources the m m 1 queue revisited")
  Member "scheduling policies for age minimization in wireless networks with unknown channel state":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "timely updates by multiple sources the m m 1 queue revisited")

Question: Please tell me which class the source paper 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)