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: "survey of consistent software defined network updates"
  Abstract: Computer networks have become a critical infrastructure. In fact, networks should not only meet strict requirements in terms of correctness, availability, and performance but they should also be very flexible and support fast updates, e.g., due to policy changes, increasing traffic, or failures. This paper presents a structured survey of mechanism and protocols to update computer networks in a fast and consistent manner. In particular, we identify and discuss the different desirable consistency properties that should be provided throughout a network update, the algorithmic techniques which are needed to meet these consistency properties, and the implications on the speed and costs at which updates can be performed. We also explain the relationship between consistent network update problems and classic algorithmic optimization ones. While our survey is mainly motivated by the advent of software-defined networks and their primary need for correct and efficient update techniques, the fundamental underlying problems are not new, and we provide a historical perspective of the subject as well.

Connected through hyperedge HE-1 (induced by source paper "macs deep reinforcement learning based sdn controller synchronization policy design"):
  with members:
    - "learning the optimal synchronization rates in distributed sdn control architectures"
    - "impact of adaptive consistency on distributed sdn applications an empirical study"
    - "dq scheduler deep reinforcement learning based controller synchronization in distributed sdn"
    - "towards adaptive state consistency in distributed sdn control plane"
    - "action branching architectures for deep reinforcement learning"
    - "continuous control with deep reinforcement learning"
    - "dueling network architectures for deep reinforcement learning"
    - "software defined networking a comprehensive survey"

Connected through hyperedge HE-2 (induced by source paper "distributed consistent network updates in sdns local verification for global guarantees"):
  with members:
    - "on the power of preprocessing in decentralized network optimization"
    - "why and how networks should run themselves"
    - "timed consistent network updates"
    - "brief announcement on the resilience of routing tables"

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)