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: "uncertainty based information extraction in wireless sensor networks for control applications"
  Abstract: Design of control applications over wireless sensor networks (WSNs) is a challenging issue due to the bandwidth-limited communication medium, energy constraints and real-time data delivery requirements. This paper introduces a new information extraction method for WSN-based control applications, which reduces the number of required data transmissions to save energy and avoid data congestion. According to the proposed approach, control applications recognize when new data readings have to be collected and determine sensor nodes that have to be activated on the basis of uncertainty analysis. Processing of the selectively collected input data is based on definition of information granules that describe state of the controlled system as well as performance of particular control decisions. This method was implemented for object tracking in WSNs. The task is to control movement of a mobile sink, which has to reach a target in the shortest possible time. Extensive simulation experiments were performed to compare performance of the proposed approach against state-of-the-art methods. Results of the experiments show that the presented information extraction method allows for substantial reduction in the amount of transmitted data with no significant negative effect on tracking performance.

Connected through hyperedge HE-1 (induced by source paper "communication aware algorithms for target tracking in wireless sensor networks"):
  with members:
    - "optimizing data collection for object tracking in wireless sensor networks"
    - "uncertainty dependent data collection in vehicular sensor networks"

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)