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: "rcanopus making canopus resilient to failures and byzantine faults"
  Abstract: Distributed consensus is a key enabler for many distributed systems including distributed databases and blockchains. Canopus is a scalable distributed consensus protocol that ensures that live nodes in a system agree on an ordered sequence of operations (called transactions). Unlike most prior consensus protocols, Canopus does not rely on a single leader. Instead, it uses a virtual tree overlay for message dissemination to limit network traffic across oversubscribed links. It leverages hardware redundancies, both within a rack and inside the network fabric, to reduce both protocol complexity and communication overhead. These design decisions enable Canopus to support large deployments without significant performance degradation. #R##N#The existing Canopus protocol is resilient in the face of node and communication failures, but its focus is primarily on performance, so does not respond well to other types of failures. For example, the failure of a single rack of servers causes all live nodes to stall. The protocol is also open to attack by Byzantine nodes, which can cause different live nodes to conclude the protocol with different transaction orders. In this paper, we describe RCanopus (`resilent Canopus') which extends Canopus to add liveness, that is, allowing live nodes to make progress, when possible, despite many types of failures. This requires RCanopus to accurately detect and recover from failure despite using unreliable failure detectors, and tolerance of Byzantine attacks. Second, RCanopus guarantees safety, that is, agreement amongst live nodes of transaction order, in the presence of Byzantine attacks and network partitioning.

Connected through hyperedge HE-1 (induced by source paper "fastfabric scaling hyperledger fabric to 20 000 transactions per second"):
  with members:
    - "hotstuff bft consensus in the lens of blockchain"
    - "trusted multi party computation and verifiable simulations a scalable blockchain approach"
    - "hyperledger fabric a distributed operating system for permissioned blockchains"
    - "how to databasify a blockchain the case of hyperledger fabric"
    - "consensus in the age of blockchains"
    - "a byzantine fault tolerant ordering service for the hyperledger fabric blockchain platform"
    - "blockbench a framework for analyzing private blockchains"

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.DC(Distributed, Parallel, and Cluster Computing)