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: "proteus a scalable bft consesus protocol for blockchains"
  Abstract: Byzantine Fault Tolerant (BFT) consensus exhibits higher throughput in comparison to Proof of Work (PoW) in blockchains. But BFT-based protocols suffer from scalability problems with respect to the number of replicas in the network. The main reason for this limitation is the quadratic message complexity of BFT protocols. Previously, proposed solutions improve BFT performance for normal operation, but will fall back to quadratic message complexity once the protocol observes a certain number of failures. This makes the protocol performance unpredictable as it is not guaranteed that the network will face a a certain number of failures. #R##N#As a result, such protocols are only scalable when conditions are favorable (i.e., the number of failures are less than a given threshold). To address this issue we propose Proteus, a new BFT-based consensus protocol which elects a subset of nodes $c$ as a root committee. Proteus guarantees stable performance, regardless of the number of failures in the network and it improves on the quadratic message complexity of typical BFT-based protocols to $O(cn)$, where $c<<n$, for large $n$. #R##N#Thus, message complexity remains small and less than quadratic when $c$ is asymptotically smaller than $n$, and this helps the protocol to provide stable performance even during the view change process (change of root committee). Our view change process is different than typical BFT protocols as it replaces the whole root committee compared to replacing a single primary in other protocols. We deployed and tested our protocol on $200$ Amazon $EC2$ instances, with two different baseline BFT protocols (PBFT and Bchain) for comparison. In these tests, our protocol outperformed the baselines by more than $2\times$ in terms of throughput as well as latency.

Connected through hyperedge HE-1 (induced by source paper "a secure consensus protocol for sidechains"):
  with members:
    - "selfish mining in ethereum"
    - "flash efficient dynamic routing for offchain networks"
    - "sbft a scalable and decentralized trust infrastructure"
    - "hotstuff bft consensus in the lens of blockchain"
    - "routing cryptocurrency with the spider network"
    - "a scale out blockchain for value transfer with spontaneous sharding"
    - "window based bft blockchain consensus"
    - "sprites and state channels payment networks that go faster than lightning"

Connected through hyperedge HE-2 (induced by source paper "flow separating consensus and compute"):
  with members:
    - "ekiden a platform for confidentiality preserving trustworthy and performant smart contracts"
    - "scalable byzantine consensus via hardware assisted secret sharing"
    - "hotstuff bft consensus in the lens of blockchain"
    - "sbft a scalable decentralized trust infrastructure for blockchains"
    - "betting on blockchain consensus with fantomette"
    - "proof of work without all the work"
    - "consensus in the age of blockchains"

Connected through hyperedge HE-3 (induced by source paper "a permit based optimistic byzantine ledger"):
  with members:
    - "the latest gossip on bft consensus"
    - "hotstuff bft consensus in the lens of blockchain"
    - "correction to byzantine agreement in expected polynomial time jacm 2016"
    - "sbft a scalable decentralized trust infrastructure for blockchains"
    - "practical synchronous byzantine consensus"
    - "efficient synchronous byzantine consensus"

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)