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 "closed form analysis of non linear age of information in status updates with an energy harvesting transmitter"):
  Abstract: Timely status updates are crucial to enabling applications in massive Internet of Things (IoT). This paper measures the data-freshness performance of a status update system with an energy harvesting transmitter, considering the randomness in information generation, transmission and energy harvesting. The performance is evaluated by a non-linear function of age of information (AoI) that is defined as the time elapsed since the generation of the most up-to-date status information at the receiver. The system is formulated as two queues with status packet generation and energy arrivals both assumed to be Poisson processes. With negligible service time, both First-Come-First-Served (FCFS) and Last-Come-First-Served (LCFS) disciplines for arbitrary buffer and battery capacities are considered, and a method for calculating the average penalty with non-linear penalty functions is proposed. The average AoI, the average penalty under exponential penalty function, and AoI's threshold violation probability are obtained in closed form. When the service time is assumed to follow exponential distribution, matrix geometric method is used to obtain the average peak AoI. The results illustrate that under the FCFS discipline, the status update frequency needs to be carefully chosen according to the service rate and energy arrival rate in order to minimize the average penalty.

Includes members:
  Member "a general formula for the stationary distribution of the age of information and its application to single server queues":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "timely updates by multiple sources the m m 1 queue revisited")
  Member "sampling for remote estimation through queues age of information and beyond":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "urgency of information for context aware timely status updates in remote control systems")
  Member "scheduling policies for minimizing age of information in broadcast wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "who should google scholar update more often")
  Member "can decentralized status update achieve universally near optimal age of information in wireless multiaccess channels":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "timely updates by multiple sources the m m 1 queue revisited")
  Member "sampling for data freshness optimization non linear age functions":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "urgency of information for context aware timely status updates in remote control systems")
  Member "age of information in g g 1 1 systems":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "who should google scholar update more often")
  Member "delay and peak age violation probability in short packet transmissions":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "optimized age of information tail for ultra reliable low latency communications in vehicular networks")
  Member "age minimal transmission for energy harvesting sensors with finite batteries online policies":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "urgency of information for context aware timely status updates in remote control systems")

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)