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: "a profit maximizing strategy of network resource management for 5g tenant slices"
  Abstract: Supported by the emerging technologies of Network Function Virtualization (NFV) and network slicing, 5G networks allow tenants to rent resources from mobile network operators (MNOs) in order to provide services without possessing an own network infrastructure. The MNOs are therefore facing the problem of deciding if to accept or decline the resource renting requests they receive. This paper builds a stochastic model that describes the MNO's revenue and opportunity cost of accepting a contract, and therewith proposes a strategy that is analytically derived to maximize the expected profit at every decision.

Connected through hyperedge HE-1 (induced by source paper "5g network slicing using sdn and nfv a survey of taxonomy architectures and future challenges"):
  with members:
    - "a novel qoe aware sdn enabled nfv based management architecture for future multimedia applications on 5g systems"
    - "securing fog to things environment using intrusion detection system based on ensemble learning"
    - "wireless network slicing generalized kelly mechanism based resource allocation"
    - "resource orchestration of 5g transport networks for vertical industries"
    - "slice as an evolutionary service genetic optimization for inter slice resource management in 5g networks"
    - "network slicing based 5g and future mobile networks mobility resource management and challenges"
    - "network slicing for 5g with sdn nfv concepts architectures and challenges"
    - "a survey on mobile edge computing the communication perspective"

Connected through hyperedge HE-2 (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"
    - "rational impatience admission control in 5g sliced networks shall i bide my slice opportunity"
    - "statistical multiplexing and traffic shaping games for network slicing"
    - "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)