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: "morph an adaptive framework for efficient and byzantine fault tolerant sdn control plane"
  Abstract: Current approaches to tackle the single point of failure in SDN entail a distributed operation of SDN controller instances. Their state synchronization process is reliant on the assumption of a correct decision-making in the controllers. Successful introduction of SDN in the critical infrastructure networks also requires catering to the issue of  unavailable ,  unreliable  (e.g. buggy), and  malicious  controller failures. We propose MORPH, a framework tolerant to unavailability and Byzantine failures, which distinguishes and localizes faulty controller instances and appropriately reconfigures the control plane. Our controller-switch connection assignment leverages the awareness of the source of failure to optimize the number of active controllers and minimize the controller and switch reconfiguration delays. The proposed re-assignment executes dynamically after each successful failure identification. We require    $2F_{M}+F_{A}+1$    controllers to tolerate    $F_{M}$    malicious and    $F_{A}$    availability-induced failures. After a successful detection of    $F_{M}$    malicious controllers, MORPH reconfigures the control plane to require a  single  controller message to forward the system state. Moreover, we outline and present a solution to the practical correctness issues related to the  statefulness  of the distributed SDN controller applications, previously ignored in the literature. We base our performance analysis on a resource-aware routing application, deployed in an emulated testbed comprising up to 16 controllers and up to 34 switches, so to tolerate up to 5 unique Byzantine and additional 5 availability-induced controller failures (a total of 10 unique controller failures). We quantify and highlight the dynamic decrease in the packet and CPU load and the response time after each successful failure detection.

Connected through hyperedge HE-1 (induced by source paper "effective scaling of blockchain beyond consensus innovations and moore s law"):
  with members:
    - "concurrency and privacy with payment channel networks"
    - "scalable byzantine consensus via hardware assisted secret sharing"
    - "blockchain goes green an analysis of blockchain on low power nodes"
    - "an energy efficient reconfigurable dtls cryptographic engine for securing internet of things applications"
    - "towards scaling blockchain systems via sharding"
    - "a scale out blockchain for value transfer with spontaneous sharding"
    - "scaling nakamoto consensus to thousands of transactions per second"
    - "blockbench a framework for analyzing private blockchains"

Connected through hyperedge HE-2 (induced by source paper "bft protocols for heterogeneous resource allocations in distributed sdn control plane"):
  with members:
    - "scalable byzantine consensus via hardware assisted secret sharing"
    - "response time and availability study of raft consensus in distributed sdn control plane"
    - "dynamic switch controller association and control devolution for sdn systems"

Connected through hyperedge HE-3 (induced by source paper "joint switch upgrade and controller deployment in hybrid software defined networks"):
  with members:
    - "divide and conquer partitioning ospf networks with sdn"
    - "software defined networking a comprehensive survey"
    - "on uniform capacitated k median beyond the natural lp relaxation"

Connected through hyperedge HE-4 (induced by source paper "p4bft hardware accelerated byzantine resilient network control plane"):
  with members:
    - "bft protocols for heterogeneous resource allocations in distributed sdn control plane"
    - "response time and availability study of raft consensus in distributed sdn control plane"
    - "paxos made switch y"

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)