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: "beamsteering on mobile devices network capacity and client efficiency"
  Abstract: Current and emerging mobile devices are omni directional in wireless communication. Such omni directionality not only limits device energy efficiency but also poses a significant challenge toward the capacity of wireless networks through inter-link interference. In this work, we seek to make mobile clients directional with beamsteering. We first demonstrate that beamsteering is already feasible to mobile devices such as Netbooks and eBook readers in terms of form factor, power efficiency, and device mobility. We further reveal that beamsteering mobile clients face a unique challenge to balance client efficiency and network capacity. There is an optimal operating point for a beamsteering mobile client in terms of the number of antennas and transmit power that achieve the required capacity with lowest power. Finally, we provide a distributed algorithm called BeamAdapt that allows each client to closely approach its optimal point iteratively without central coordination. We also offer a cellular system realization of BeamAdapt. Using Qualnet-based simulation, we show that BeamAdapt with four antennas can reduce client power consumption by 55% while maintaining a required network throughput for a large-scale network, compared to the same network with omni directional mobile clients.

Connected through hyperedge HE-1 (induced by source paper "quantifying potential energy efficiency gain in green cellular wireless networks"):
  with members:
    - "predictive green wireless access exploiting mobility and application information"
    - "exploiting network cooperation in green wireless communication"
    - "green cellular networks a survey some research issues and challenges"
    - "a survey of green networking research"
    - "femtocell networks a survey"

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)