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: "flow separating consensus and compute"
  Abstract: Throughput limitations of existing blockchain architectures are one of the most significant hurdles for their wide-spread adoption. Attempts to address this challenge include layer-2 solutions, such as Bitcoin's Lightning or Ethereum's Plasma network, that move work off the main chain. Another prominent technique is sharding, i.e., breaking the network into many interconnected networks. However, these scaling approaches significantly increase the complexity of the programming model by breaking ACID guarantees increasing the cost and time for application development. #R##N#In this paper, we describe a novel approach where we split the work traditionally assigned to cryptocurrency miners into two different node roles. Specifically, the selection and ordering of transactions are performed independently from their execution. The focus of this paper is to formalize the split of consensus and computation, and prove that this approach increases throughput without compromising security. #R##N#In contrast to most existing proposals, our approach achieves scaling via separation of concerns, i.e., better utilization of network resources, rather than sharding. This approach allows established programming paradigms for smart contracts (which generally assume transactional atomicity) to persist without introducing additional complexity. We present simulations on a proof-of-concept network of 32 globally distributed nodes. While the consensus algorithm was identical in all simulations (a 2-step-commit protocol with rotating block proposer), block computation was either included in a consensus nodes' regular operations (conventional architecture) or delegated to specialized execution nodes (separation of concerns). Separation of concerns enables our system to achieve a throughput increase by a factor of 56 compared to conventional architectures without loss of safety or decentralization.

Connected through hyperedge HE-1 (induced by source paper "flow separating consensus and compute block formation and execution"):
  with members:
    - "flow separating consensus and compute execution verification"
    - "dfinity technology overview series consensus system"
    - "hotstuff bft consensus in the lens of blockchain"

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)