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 "stochastic online control for energy harvesting wireless networks with battery imperfections"):
  Abstract: In energy harvesting (EH) network, the energy storage devices (i.e., batteries) are usually not perfect. In this paper, we consider a practical battery model with finite battery capacity, energy (dis-)charging loss, and energy dissipation. Taking into account such battery imperfections, we rely on the Lyapunov optimization technique to develop a stochastic online control scheme that aims to maximize the utility of data rates for EH multi-hop wireless networks. It is established that the proposed algorithm can provide a feasible and efficient data admission, power allocation, routing and scheduling solution, without requiring any statistical knowledge of the stochastic channel, data-traffic, and EH processes. Numerical results demonstrate the merit of the proposed scheme.

Includes members:
  Member "energy harvesting broadband communication systems with processing energy cost":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "flexible functional split and power control for energy harvesting cloud radio access networks")
  Member "throughput maximization for the gaussian relay channel with energy harvesting constraints":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "timely updates in energy harvesting two hop networks offline and online policies")
  Member "a learning theoretic approach to energy harvesting communication system optimization":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a survey on machine learning based performance improvement of wireless networks phy mac and network layer")
  Member "optimal scheduling and power allocation for two hop energy harvesting communication systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "single or multiple frames content delivery for robust and secure communication in energy and spectrum efficient 5g networks")
  Member "throughput optimal policies for energy harvesting wireless transmitters with non ideal circuit power":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a maximin optimal online power control policy for energy harvesting communications")
  Member "optimal save then transmit protocol for energy harvesting wireless transmitters":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "mimo underlay cognitive radio optimized power allocation effective number of transmit antennas and harvest transmit tradeoff")
  Member "broadcasting with an energy harvesting rechargeable transmitter":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "age of information minimization for an energy harvesting source with updating erasures with and without feedback")
  Member "sum rate optimal power policies for energy harvesting transmitters in an interference channel":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "age minimal online policies for energy harvesting sensors with random battery recharges")

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)