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 "energy neutral source channel coding with battery and memory size constraints"):
  Abstract: We study energy management policies for the compression and transmission of source data collected by an energy-harvesting sensor node with a finite energy buffer (e.g., rechargeable battery) and a finite data buffer (memory) between source encoder and channel encoder. The sensor node can adapt the source and channel coding rates depending on the observation and channel states. In such a system, the absence of precise information about the amount of energy available in the future is a key challenge. We provide analytical bounds and scaling laws for the average distortion that depend on the size of the energy and data buffers. We furthermore design a resource allocation policy that achieves almost optimal distortion scaling. Our results demonstrate that the energy leakage of state of art energy management policies can be avoided by jointly controlling the source and channel coding rates.

Includes members:
  Member "dynamic compression transmission for energy harvesting multihop networks with correlated sources":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "reconstruction of correlated sources with energy harvesting constraints in delay constrained and delay tolerant communication scenarios")
  Member "energy management policies for energy neutral source channel coding":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "stochastic routing and scheduling policies for energy harvesting communication networks")
  Member "optimal energy allocation for wireless communications with energy harvesting constraints":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "optimal energy allocation and task offloading policy for wireless powered mobile edge computing systems")
  Member "stability and capacity regions or discrete time queueing networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "predictive control and communication co design a gaussian process regression approach")
  Member "basic performance limits and tradeoffs in energy harvesting sensor nodes with finite data and energy storage":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the energy and data storage management in energy harvesting wireless communications")

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)