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: "guaranteeing qos using unlicensed tv white spaces for smart grid applications"
  Abstract: In this paper, we consider the utilization of TV White Spaces (TVWS) by small Cognitive Radio (CR) network operators to support the communication needs of various smart grid applications. We first propose a multi-tier communication network architecture for smart metering applications in dense urban environments. Our measurement campaign, without any competition from other CR operators, reveals that the communication architecture can achieve more than 1Mbps data rates using the free unlicensed TVWS spectrum. However, anticipating stiff competition for the unlicensed TVWS spectrum among CR operators and to support smart grid applications with stringent Quality of Service (QoS) requirements, we further exploit the novel idea of high priority channels (HPC) that the CR operator can temporarily lease by paying a small fee. This poses several new challenges for the CR operators, such as, their economic viability while providing QoS guarantees. We develop a real-time decision support framework with several adjustable parameters for the CR operators that enables them to tradeoff HPC leasing cost and QoS. The developed algorithms are simple rules that provide significant opportunities to the CR operators to maintain a balance between spectrum cost and QoS depending on dynamic spectrum availability and smart grid application requirements.

Connected through hyperedge HE-1 (induced by source paper "exploiting qos flexibility for smart grid and iot applications using tv white spaces extended version"):
  with members:
    - "design of a scalable hybrid mac protocol for heterogeneous m2m 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)