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: "evaluating the performance of emtc and nb iot for smart city applications"
  Abstract: Low power wide area network (LPWAN) is a wireless telecommunication network that is designed for interconnecting devices with low bitrate focusing on long range and power efficiency. In this paper, we study two recent technologies built from existing Long-Term Evolution (LTE) functionalities: Enhanced machine type communications (eMTC) and Narrow band internet of things (NB-IoT). These technologies are designed to coexist with existing LTE infrastructure, spectrum, and devices. We first briefly introduce both systems and then compare their performance in terms of energy consumption, latency and scalability. We introduce a model for calculating the energy consumption and study the effect of clock drift and propose a method to overcome it. We also propose a model for analytically evaluating the latency and the maximum number of devices in a network. Furthermore, we implement the main functionality of both technologies and simulate the end-to-end latency and maximum number of devices in a discrete-event network simulator NS-3. Numerical results show that 8 years battery life time can be achieved by both technologies in a poor coverage scenario and that depending on the coverage conditions and data length, one technology consumes less energy than the other. The results also show that eMTC can serve more devices in a network than NB-IoT, while providing a latency that is 10 times lower.

Connected through hyperedge HE-1 (induced by source paper "3d multi drone cell trajectory design for efficient iot data collection"):
  with members:
    - "on the number and 3d placement of drone base stations in wireless cellular networks"
    - "a tutorial on uavs for wireless networks applications challenges and open problems"
    - "air ground integrated vehicular network slicing with content pushing and caching"
    - "joint trajectory and communication design for multi uav enabled wireless networks"
    - "mobile unmanned aerial vehicles uavs for energy efficient internet of things communications"
    - "backhaul aware robust 3d drone placement in 5g wireless networks"
    - "energy efficient uav communication with trajectory optimization"

Connected through hyperedge HE-2 (induced by source paper "evaluation modeling and optimization of coverage enhancement methods of nb iot"):
  with members:
    - "analytic analysis of narrowband iot coverage enhancement approaches"

Connected through hyperedge HE-3 (induced by source paper "latency energy tradeoff based on channel scheduling and repetitions in nb iot systems"):
  with members:
    - "self organized low power iot networks a distributed learning approach"
    - "an enhanced access reservation protocol with a partial preamble transmission mechanism in nb iot systems"
    - "narrowband iot data transmission procedures for massive machine type communications"
    - "optimized lte data transmission procedures for iot device side energy consumption analysis"
    - "random access preamble design and detection for 3gpp narrowband iot systems"
    - "adaptive drx scheme to improve energy efficiency in lte networks with bounded delay"
    - "assessment of lte wireless access for monitoring of energy distribution in the smart grid"

Connected through hyperedge HE-4 (induced by source paper "exploring the performance boundaries of nb iot"):
  with members:
    - "analytic analysis of narrowband iot coverage enhancement approaches"
    - "narrowband iot data transmission procedures for massive machine type communications"
    - "low power wide area networks an overview"

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.IT(Information Theory)