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: "empiot an energy measurement platform for wireless iot devices"
  Abstract: Profiling and minimizing the energy consumption of IoT devices is an essential step towards employing IoT in various application domains. In this paper we propose EMPIOT, an accurate, low-cost, easy to build, and flexible, power measurement platform. We present the hardware and software components of this platform, and study the effect of various design parameters on accuracy. In particular, we analyze the effect of driver, bus speed, input voltage, and buffering mechanism, on sampling rate, measurement accuracy and processing demand. These extensive experimental studies enable us to configure the system in order to achieve its highest performance. We also propose a novel calibration technique and report the calibration parameters under various settings. Using five different IoT devices performing four types of workloads, we evaluate the performance of EMPIOT against the ground truth obtained from high-accuracy devices. Our results show that, for very low-power devices that utilize 802.15.4 wireless standard, measurement error is less than 4%. In addition, for 802.11-based devices that generate short and high power spikes, error is less than 3%.

Connected through hyperedge HE-1 (induced by source paper "image classification on iot edge devices profiling and modeling"):
  with members:
    - "profiling and improving the duty cycling performance of linux based iot devices"
    - "applications of deep learning and reinforcement learning to biological data"
    - "fog computing survey of trends architectures requirements and research directions"
    - "fashion mnist a novel image dataset for benchmarking machine learning algorithms"
    - "deep residual learning for image recognition"
    - "going deeper with convolutions"

Connected through hyperedge HE-2 (induced by source paper "implementation and analysis of quic for mqtt"):
  with members:
    - "a review of software defined wlans architectures and central control mechanisms"
    - "evaluating the stream control transmission protocol using uppaal"

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)