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 "near optimal online distortion minimization for energy harvesting nodes"):
  Abstract: We consider online scheduling for an energy harvesting communication system where a sensor node collects samples from a Gaussian source and sends them to a destination node over a Gaussian channel. The sensor is equipped with a finite-sized battery that is recharged by an independent and identically distributed (i.i.d.) energy harvesting process over time. The goal is to minimize the long term average distortion of the source samples received at the destination. We study two problems: the first is when sampling is cost-free, and the second is when there is a sampling cost incurred whenever samples are collected. We show that fixed fraction policies [Shaviv-Ozgur], in which a fixed fraction of the battery state is consumed in each time slot, are near-optimal in the sense that they achieve a long term average distortion that lies within a constant additive gap from the optimal solution for all energy arrivals and battery sizes. For the problem with sampling costs, the transmission policy is bursty; the sensor can collect samples and transmit for only a portion of the time.

Includes members:
  Member "optimal offline and competitive online strategies for transmitter receiver energy harvesting":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "online energy harvesting problem over an arbitrary directed acyclic graph network")
  Member "optimal policies for wireless networks with energy harvesting transmitters and receivers effects of decoding costs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "joint energy and sinr coverage in spatially clustered rf powered iot network")
  Member "iterative dynamic water filling for fading multiple access channels with energy harvesting":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "design of an miso swipt aided code index modulated multi carrier m dcsk system for e health iot")
  Member "source channel coding under energy delay and buffer constraints":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "leveraging linear quadratic regulator cost and energy consumption for ultra reliable and low latency iot control systems")
  Member "energy harvesting networks with energy cooperation procrastinating policies":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "real time transmission mechanism design for wireless iot sensors with energy harvesting under power saving mode")
  Member "universally near optimal online power control for energy harvesting nodes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a maximin optimal online power control policy for energy harvesting communications")
  Member "energy harvesting broadband communication systems with processing energy cost":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "flexible functional split and power control for energy harvesting cloud radio access networks")
  Member "energy cooperation in energy harvesting communications":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "transmission delay minimization in wireless powered communication 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)