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: "cross layer software defined 5g network"
  Abstract: In the past few decades, the world has witnessed a rapid growth in mobile communication and reaped great benefits from it. Even though the fourth generation (4G) mobile communication system is just being deployed worldwide, proliferating mobile demands call for newer wireless communication technologies with even better performance. Consequently, the fifth generation (5G) system is already emerging in the research field. However, simply evolving the current mobile networks can hardly meet such great expectations, because over the years the infrastructures have generally become ossified, closed, and vertically constructed. Aiming to establish a new paradigm for 5G mobile networks, in this article, we propose a cross-layer software-defined 5G network architecture. By jointly considering both the network layer and the physical layer together, we establish the two software-defined programmable components, the control plane and the cloud computing pool, which enable an effective control of the mobile network from the global perspective and benefit technological innovations. Specifically, by the cross-layer design for software-defining, the logically centralized and programmable control plane abstracts the control functions from the network layer down to the physical layer, through which we achieve the fine-grained controlling of mobile network, while the cloud computing pool provides powerful computing capability to implement the baseband data processing of multiple heterogeneous networks. The flexible programmability feature of our architecture makes it convenient to deploy cross-layer technological innovations and benefits the network evolution. We discuss the main challenges of our architecture, including the fine-grained control strategies, network virtualization, and programmability. The architecture significantly benefits the convergence towards heterogeneous networks and enables much more controllable, programmable and evolvable mobile networks. Simulations validate these performance advantages.

Connected through hyperedge HE-1 (induced by source paper "qoe management of multimedia streaming services in future networks a tutorial and survey"):
  with members:
    - "5g network slicing using sdn and nfv a survey of taxonomy architectures and future challenges"
    - "a novel qoe aware sdn enabled nfv based management architecture for future multimedia applications on 5g systems"
    - "mptcp meets fec supporting latency sensitive applications over heterogeneous networks"
    - "network slicing for 5g with sdn nfv concepts architectures and challenges"
    - "nfv and sdn key technology enablers for 5g networks"
    - "network slicing to enable scalability and flexibility in 5g mobile networks"
    - "balancing the migration of virtual network functions with replications in data centers"
    - "5g icn delivering icn services over 5g using network slicing"

Connected through hyperedge HE-2 (induced by source paper "will sdn be part of 5g"):
  with members:
    - "5g fronthaul latency and jitter studies of cpri over ethernet"
    - "r fft function split at ifft fft in unified lte cran and cable access network"
    - "nfv and sdn key technology enablers for 5g networks"
    - "hardware accelerated sdr platform for adaptive air interfaces"
    - "srslte an open source platform for lte evolution and experimentation"
    - "software defined optical networks sdons a comprehensive survey"
    - "are heterogeneous cloud based radio access networks cost effective"
    - "fronthaul constrained cloud radio access networks insights and challenges"

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)