human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "competition between tenants with strategic resource allocation in 5g network slicing"):
  Abstract: We propose and analyze a business model for 5G operators. Each operator is entitled to a share of a network operated by an Infrastructure Provider (InP) and use network slicing mechanisms to request network resources as needed for service provision. The network operators become Network Slice Tenants (NSTs). The InP performs the resource allocation based on a vector of weights chosen strategically by each NST. The weights distribute the NST's share of resources between its subscribers in each cell. We propose a strategy profile in which the NST chooses weights equal to the product of its share by the ratio between the total number of subscribers in the cell and the total number of subscribers in the network. We characterize the proposed solution in terms of subscription ratios and fractions of subscribers, for different cell capacities and user sensitivities. The proposed solution provides the exact values for the Nash equilibrium if the cells are homogeneous in terms of normalized capacity, which is a measure of the total amount of resources available in the cell. Otherwise, if the cells are heterogeneous, it provides an accurate approximation. We quantify the deviation from the equilibrium and conclude that it is highly accurate.

Includes members:
  Member "from network sharing to multi tenancy the 5g network slice broker":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "5g network slicing using sdn and nfv a survey of taxonomy architectures and future challenges")
  Member "network slicing games enabling customization in multi tenant networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "machine learning for network slicing resource management a comprehensive survey")

Question: Please tell me which class the source paper 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)