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: "sky opinion dynamics based consensus for p2p network with trust relationships"
  Abstract: Traditional Byzantine consensus does not work in P2P network due to Sybil attack while the most prevalent Sybil-proof consensus at present still can't resist adversary with dominant compute power. This paper proposed opinion dynamics based consensus for P2P network with trust relationships, consisting of the sky framework and the sky model. With the sky framework, opinion dynamics can be applied in P2P network for consensus which is Sybil-proof through trust relationships and emerges from local interactions of each node with its direct contacts without topology, global information or even sample of the network involved. The sky model has better performance of convergence than existing models including MR, voter and Sznajd, and its lower bound of fault tolerance performance is also analyzed and proved. Simulations show that our approach can tolerant failures by at least 13% random nodes or 2% top influential nodes while over 96% correct nodes still make correct decision within 70 seconds on the SNAP Wikipedia who-votes-on-whom network for initial configuration of convergence>0.5 with reasonable latencies. Comparing to compute power based consensus, our approach can resist any faulty or malicious nodes by unfollowing them. To the best of our knowledge, it's the first work to bring opinion dynamics to P2P network for consensus.

Connected through hyperedge HE-1 (induced by source paper "skyhash a hash opinion dynamics model"):
  with members:
    - "sky an opinion dynamics framework and model for consensus over p2p network"
    - "on subversive miner strategies and block withholding attack in bitcoin digital currency"
    - "the impact of network flows on community formation in models of opinion dynamics"

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)