human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "reconstruction of correlated sources with energy harvesting constraints in delay constrained and delay tolerant communication scenarios"
  Abstract: In this paper, we investigate the reconstruction of time-correlated sources in a point-to-point communications scenario comprising an energy-harvesting sensor and a Fusion Center (FC). Our goal is to minimize the average distortion in the reconstructed observations by using data from previously encoded sources as side information. First, we analyze a delay-constrained scenario, where the sources must be reconstructed before the next time slot. We formulate the problem in a convex optimization framework and derive the optimal transmission (i.e., power and rate allocation) policy. To solve this problem, we propose an iterative algorithm based on the subgradient method. Interestingly, the solution to the problem consists of a coupling between a two-dimensional directional water-filling algorithm (for power allocation) and a reverse water-filling algorithm (for rate allocation). Then we find a more general solution to this problem in a delay-tolerant scenario where the time horizon for source reconstruction is extended to multiple time slots. Finally, we provide some numerical results that illustrate the impact of delay and correlation in the power and rate allocation policies, and in the resulting reconstruction distortion. We also discuss the performance gap exhibited by a heuristic online policy derived from the optimal (offline) one.

Connected through hyperedge HE-1 (induced by source paper "stochastic routing and scheduling policies for energy harvesting communication networks"):
  with members:
    - "sensor selection and power allocation strategies for energy harvesting wireless sensor networks"
    - "energy harvesting wireless communications a review of recent advances"
    - "source channel coding under energy delay and buffer constraints"
    - "energy harvesting two hop communication networks"
    - "information and energy cooperation in cognitive radio networks"
    - "secrecy wireless information and power transfer with miso beamforming"
    - "multiuser miso beamforming for simultaneous wireless information and power transfer"
    - "simultaneous information and power transfer for broadband wireless systems"

Connected through hyperedge HE-2 (induced by source paper "joint retransmission compression and channel coding for data fidelity under energy constraints"):
  with members:
    - "energy harvesting wireless communications a review of recent advances"
    - "data driven stochastic models and policies for energy harvesting sensor communications"
    - "solarstat modeling photovoltaic sources through stochastic markov processes"
    - "secure layered transmission in multicast systems with wireless information and power transfer"
    - "a learning theoretic approach to energy harvesting communication system optimization"
    - "energy management policies for energy neutral source channel coding"

Question: Please tell me which class the center node 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)