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: "energy efficient scheduling for mmwave backhauling of small cells in heterogeneous cellular networks"
  Abstract: Heterogeneous cellular networks with small cells densely deployed underlying the conventional homogeneous macrocells are emerging as a promising candidate for the fifth generation (5G) mobile network. When a large number of base stations are deployed, the cost-effective, flexible, and green backhaul solution becomes one of the most urgent and critical challenges. With vast amounts of spectrum available, wireless backhaul in the millimeter wave (mmWave) band is able to provide several-Gbps transmission rates. To overcome high propagation loss at higher frequencies, mmWave backhaul utilize beamforming to achieve directional transmission, and concurrent transmissions (spatial reuse) under low inter-link interference can be enabled to significantly improve network capacity. To achieve an energy efficient solution for the mmWave backhauling of small cells, we first formulate the problem of minimizing the energy consumption via concurrent transmission scheduling and power control into a mixed integer nonlinear programming problem. Then we develop an energy efficient and practical mmWave backhauling scheme, where the maximum independent set based scheduling algorithm and the power control algorithm are proposed to exploit the spatial reuse for low energy consumption and high energy efficiency. We also theoretically analyze the conditions that our scheme reduces energy consumption, and the choice of the interference threshold for energy reduction. Through extensive simulations under various traffic patterns and system parameters, we demonstrate the superior performance of our scheme in terms of energy consumption and energy efficiency, and also analyze the choice of the interference threshold under different traffic loads, BS distributions, and the maximum transmission power.

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.NI(Networking and Internet Architecture)