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: "rational impatience admission control in 5g sliced networks shall i bide my slice opportunity"
  Abstract: Recently, the specifications of the fifth generation (5G) of mobile networks have been released witnessing the industrial interest around the novel network slicing concept. This context is further enriched by the evolution of an emerging type of public cloud environment: the Slice-as-a-Service (SlaaS). Infrastructure providers or network operators deploy different admission strategy while processing network slice requests issued by infrastructure tenants based on service level agreements (SLAs) and current (and predicted) resource availability. #R##N#However, when the service demand will reasonably get dense, congestions of slice requests may occur leading to long waiting periods. This may turn into impatient tenant behaviors that mitigate potential loss. This paper studies the rational strategies of impatient tenants waiting in queue-based slice admission control system, proving mathematically and empirically the benefits of allowing infrastructure provider to share its information with the upcoming tenants.

Connected through hyperedge HE-1 (induced by source paper "machine learning for network slicing resource management a comprehensive survey"):
  with members:
    - "a utility driven multi queue admission control solution for network slicing"
    - "a markov model of slice admission control"
    - "slice as an evolutionary service genetic optimization for inter slice resource management in 5g networks"
    - "statistical multiplexing and traffic shaping games for network slicing"
    - "a profit maximizing strategy of network resource management for 5g tenant slices"
    - "network slicing games enabling customization in multi tenant 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)