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 for service oriented networks under resource constraints"
  Abstract: To support multiple on-demand services over fixed communication networks, network operators must allow flexible customization and fast provision of their network resources. One effective approach to this end is network virtualization, whereby each service is mapped to a virtual subnetwork providing dedicated on-demand support to network users. In practice, each service consists of a prespecified sequence of functions, called a service function chain (SFC), while each service function in a SFC can only be provided by some given network nodes. Thus, to support a given service, we must select network function nodes according to the SFC and determine the routing strategy through the function nodes in a specified order. A crucial network slicing problem that needs to be addressed is how to optimally localize the service functions in a physical network as specified by the SFCs, subject to link and node capacity constraints. In this paper, we formulate the network slicing problem as a mixed binary linear program and establish its strong NP-hardness. Furthermore, we propose efficient penalty successive upper bound minimization (PSUM) and PSUM-R(ounding) algorithms, and two heuristic algorithms to solve the problem. Simulation results are shown to demonstrate the effectiveness of the proposed algorithms.

Connected through hyperedge HE-1 (induced by source paper "coexistence mechanism between embb and urllc in 5g wireless networks"):
  with members:
    - "embb urllc resource slicing a risk sensitive approach"
    - "coexistence of urllc and embb services in the c ran uplink an information theoretic study"
    - "5g wireless network slicing for embb urllc and mmtc a communication theoretic view"
    - "ultra reliable and low latency communications in 5g downlink physical layer aspects"
    - "joint scheduling of urllc and embb traffic in 5g wireless networks"
    - "resource scheduling for mixed traffic types with scalable tti in dynamic tdd systems"
    - "the dispersion of nearest neighbor decoding for additive non gaussian channels"
    - "a quantitative measure of fairness and discrimination for resource allocation in shared computer systems"

Connected through hyperedge HE-2 (induced by source paper "a virtual network customization framework for multicast services in nfv enabled core networks"):
  with members:
    - "air ground integrated vehicular network slicing with content pushing and caching"
    - "service overlay forest embedding for software defined cloud networks"
    - "distributed service function chaining"
    - "vehicular communications a network layer perspective"
    - "service function chaining resource allocation a survey"
    - "scalable steiner tree for multicast communications in software defined networking"
    - "specifying and placing chains of virtual network functions"

Connected through hyperedge HE-3 (induced by source paper "network slicing for service oriented networks with flexible routing and guaranteed e2e latency"):
  with members:
    - "multi commodity flow with in network processing"
    - "network function virtualization state of the art and research challenges"

Connected through hyperedge HE-4 (induced by source paper "joint communication computation caching and control in big data multi access edge computing"):
  with members:
    - "deep learning for reliable mobile edge analytics in intelligent transportation systems"
    - "proactive edge computing in latency constrained fog networks"
    - "a survey on mobile edge computing the communication perspective"
    - "an online secretary framework for fog network formation with minimal latency"
    - "stochastic joint radio and computational resource management for multi user mobile edge computing systems"
    - "energy efficient resource allocation for cache assisted mobile edge computing"
    - "artificial neural networks based machine learning for wireless networks a tutorial"
    - "caching in the sky proactive deployment of cache enabled unmanned aerial vehicles for optimized quality of experience"

Connected through hyperedge HE-5 (induced by source paper "deep learning based caching for self driving car in multi access edge computing"):
  with members:
    - "the history began from alexnet a comprehensive survey on deep learning approaches"
    - "joint communication computation caching and control in big data multi access edge computing"
    - "neutm a neural network based framework for traffic matrix prediction in sdn"
    - "dager deep age gender and emotion recognition using convolutional neural network"
    - "optimal geographic caching in cellular networks"
    - "very deep convolutional networks for large scale image recognition"

Connected through hyperedge HE-6 (induced by source paper "deep reinforcement learning for resource management in network slicing"):
  with members:
    - "slice as an evolutionary service genetic optimization for inter slice resource management in 5g networks"
    - "nfv and sdn key technology enablers for 5g 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)