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 "online timely status updates with erasures for energy harvesting sensors"):
  Abstract: An energy harvesting sensor that is sending status updates to a destination through an erasure channel is considered, in which transmissions are prone to being erased with some probability $q$, independently from other transmissions. The sensor, however, is unaware of erasure events due to lack of feedback from the destination. Energy expenditure is normalized in the sense that one transmission consumes one unit of energy. The sensor is equipped with a unit-sized battery to save its incoming energy, which arrives according to a Poisson process of unit rate. The setting is online, in which energy arrival times are only revealed causally after being harvested, and the goal is to design transmission times such that the long term average age of information (AoI), defined as the time elapsed since the latest update has reached the destination successfully, is minimized. The optimal status update policy is first shown to have a renewal structure, in which the time instants at which the destination receives an update successfully constitute a renewal process. Then, for $q\leq\frac{1}{2}$, the optimal renewal policy is shown to have a threshold structure, in which a new status update is transmitted only if the AoI grows above a certain threshold, that is shown to be a decreasing function of $q$. While for $q>\frac{1}{2}$, the optimal renewal policy is shown to be greedy, in which a new status update is transmitted whenever energy is available.

Includes members:
  Member "optimal status updating for an energy harvesting sensor with a noisy channel":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "timely status updating through intermittent sensing and transmission")
  Member "coded status updates in an energy harvesting erasure channel":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "timely updates by multiple sources the m m 1 queue revisited")
  Member "status updates in a multi stream m g 1 1 preemptive queue":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "who should google scholar update more often")
  Member "age minimal online policies for energy harvesting sensors with random battery recharges":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "who should google scholar update more often")
  Member "sending information through status updates":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "age of information with gilbert elliot servers and samplers")
  Member "age minimal transmission for energy harvesting sensors with finite batteries online policies":
    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 "scheduling status updates to minimize age of information with an energy harvesting sensor":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "urgency of information for context aware timely status updates in remote control systems")
  Member "optimal status update for age of information minimization with an energy harvesting source":
    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.IT(Information Theory)