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 "minimizing the age of information in wireless networks with stochastic arrivals"):
  Abstract: We consider a wireless network with a base station serving multiple traffic streams to different destinations. Packets from each stream arrive to the base station according to a stochastic process and are enqueued in a separate (per stream) queue. The queueing discipline controls which packet within each queue is available for transmission. The base station decides, at every time t, which stream to serve to the corresponding destination. The goal of scheduling decisions is to keep the information at the destinations fresh. Information freshness is captured by the Age of Information (AoI) metric. #R##N#In this paper, we derive a lower bound on the AoI performance achievable by any given network operating under any queueing discipline. Then, we consider three common queueing disciplines and develop both an Optimal Stationary Randomized policy and a Max-Weight policy under each discipline. Our approach allows us to evaluate the combined impact of the stochastic arrivals, queueing discipline and scheduling policy on AoI. We evaluate the AoI performance both analytically and using simulations. Numerical results show that the performance of the Max-Weight policy is close to the analytical lower bound.

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 "distributed scheduling algorithms for optimizing information freshness in wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (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-4 (induced by source paper "optimizing information freshness in wireless networks a stochastic geometry approach")
  Member "scheduling policies for age minimization in wireless networks with unknown channel state":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "timely updates by multiple sources the m m 1 queue revisited")
  Member "scheduling status updates to minimize age of information with an energy harvesting sensor":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "urgency of information for context aware timely status updates in remote control systems")
  Member "age optimal information updates in multihop networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "timely updates by multiple sources the m m 1 queue revisited")
  Member "age and value of information non linear age case":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "who should google scholar update more often")

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.NI(Networking and Internet Architecture)