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: "network slicing management technique for local 5g micro operator deployments"
  Abstract: Local 5G networks are expected to emerge to serve different vertical sectors specific requirements. These networks can be deployed by traditional mobile network operators or entrant local operators. With a large number of verticals with different service requirements, while considering the network deployment cost in a single local area, it will not be economically feasible to deploy separate networks for each vertical. Thus, locally deployed 5G networks (aka micro operator networks) that can serve multiple verticals with multiple tenants in a location have gained increasing attention. Network slicing will enable a 5G micro-operator network to efficiently serve the multiple verticals and their tenants with different network requirements. This paper addresses how network slicing management functions can be used to implement, orchestrate and manage network slicing in different deployments of a local 5G micro-operator including the serving of closed, open and mixed customer groups. The paper proposes a descriptive technique by which different network slicing management functionalities defined by 3GPP can be used in coordination to create, orchestrate and manage network slicing for different deployment scenarios of a micro-operator. This is based on the network slice instance configuration type that can exist for each scenario. A network slice formation sequence is developed for the closed micro operator network to illustrate the tasks of the management functions. The results indicate that network slicing management plays a key role in designing local 5G networks that can serve different customer groups in the verticals.

Connected through hyperedge HE-1 (induced by source paper "identifying requirements affecting latency in a softwarized network for future 5g and beyond"):
  with members:
    - "a survey on low latency towards 5g ran core network and caching solutions"

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)