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: "greening geographical power allocation for cellular networks"
  Abstract: Harvesting energy from nature (solar, wind etc.) is envisioned as a key enabler for realizing green wireless networks. However, green energy sources are geographically distributed and the power amount is random which may not enough to power a base station by a single energy site. Burning brown energy sources such as coal and crude oil, though companied with carbon dioxide emission, provides stable power. In this paper, without sacrificing communication quality, we investigate how to perform green energy allocation to abate the dependence on brown energy with hybrid brown and green energy injected in power networks. We present a comprehensive framework to characterize the performance of hybrid green and brown energy empowered cellular network. Novel performance metric "bits/ton\ce{CO2}/Hz" is proposed to evaluate the greenness of the communication network. As green energy is usually generated from distributed geographical locations and is time varying, online geographical power allocation algorithm is proposed to maximize the greenness of communication network considering electricity transmission's physical laws i.e., Ohm's law and Kirchhoff's circuit laws. Simulations show that geographically distributed green energy sources complement each other by improving the communication capacity while saving brown energy consumption. Besides, the penetration of green energy can also help reduce power loss on the transmission breaches.

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)