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: "m2m massive access in lte rach performance evaluation in a smart city scenario"
  Abstract: Several studies assert that the random access procedure of the Long Term Evolution (LTE) cellular standard may not be effective whenever a massive number of simultaneous connection attempts are performed by terminals, as may happen in a typical Internet of Things or Smart City scenario. Nevertheless, simulation studies in real deployment scenarios are missing because many system-level simulators do not implement the LTE random access procedure in detail. In this paper, we propose a patch for the LTE module of ns-3, one of the most prominent open-source network simulators, to improve the accuracy of the routine that simulates the LTE Random Access Channel (RACH). The patched version of the random access procedure is compared with the default one and the issues arising from massive simultaneous access from mobile terminals in LTE are assessed via a simulation campaign.

Connected through hyperedge HE-1 (induced by source paper "a thorough study of lorawan performance under different parameter settings"):
  with members:
    - "employing p csma on a lora network simulator"
    - "uncoordinated access schemes for the iot approaches regulations and performance"
    - "does bidirectional traffic do more harm than good in lorawan based lpwa networks"
    - "analysis of latency and mac layer performance for class a lorawan"
    - "scalability analysis of large scale lorawan networks in ns 3"
    - "internet of things applications and challenges in technology and standardization"

Connected through hyperedge HE-2 (induced by source paper "spatiotemporal stochastic modeling of iot enabled cellular networks scalability and stability analysis"):
  with members:
    - "properties of an aloha like stability region"
    - "modeling and analysis of cellular networks using stochastic geometry a tutorial"
    - "on the evaluation of lte random access channel overload in a smart city scenario"
    - "analytical modeling of interference aware power control for the uplink of heterogeneous cellular networks"
    - "modeling cellular networks in fading environments with dominant specular components"
    - "tractable stochastic geometry model for iot access in lte networks"
    - "the intensity matching approach a tractable stochastic geometry approximation to system level analysis of cellular networks"
    - "are we approaching the fundamental limits of wireless network densification"

Connected through hyperedge HE-3 (induced by source paper "tractable stochastic geometry model for iot access in lte networks"):
  with members:
    - "on the evaluation of lte random access channel overload in a smart city scenario"
    - "on stochastic geometry modeling of cellular uplink transmission with truncated channel inversion power control"
    - "joint rate and sinr coverage analysis for decoupled uplink downlink biased cell associations in hetnets"

Connected through hyperedge HE-4 (induced by source paper "symbiocity smart cities for smarter networks"):
  with members:
    - "long range communications in unlicensed bands the rising stars in the iot and smart city scenarios"
    - "sensing as a service model for smart cities supported by internet of things"

Connected through hyperedge HE-5 (induced by source paper "effects of relay selection strategies on the spectral efficiency of wireless systems with half and full duplex nodes"):
  with members:
    - "on the secrecy of interference limited networks under composite fading channels"
    - "contention based geographic forwarding strategies for wireless sensors networks"
    - "in band full duplex wireless challenges and opportunities"
    - "experiment driven characterization of full duplex wireless systems"
    - "a simple cooperative diversity method based on network path selection"

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)