human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "byzantine consensus under local broadcast model tight sufficient condition"):
  Abstract: In this work we consider Byzantine Consensus on undirected communication graphs under the local broadcast model. In the classical point-to-point communication model the messages exchanged between two nodes $u, v$ on an edge $uv$ of $G$ are private. This allows a faulty node to send conflicting information to its different neighbours, a property called equivocation. In contrast, in the local broadcast communication model considered here, a message sent by node $u$ is received identically by all of its neighbours. This restriction to broadcast messages provides non-equivocation even for faulty nodes. In prior results [10, 11] it was shown that in the local broadcast model the communication graph must be $(\lfloor 3f/2 \rfloor +1)$-connected and have degree at least $2f$ to achieve Byzantine Consensus. In this work we show that this network condition is tight.

Includes members:
  Member "exact byzantine consensus under local broadcast model":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "exact byzantine consensus on undirected graphs under local broadcast model")
  Member "exact byzantine consensus in directed graphs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "exact byzantine consensus on undirected graphs under local broadcast model")
  Member "broadcast using certified propagation algorithm in presence of byzantine faults":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "determining r and r s robustness of digraphs using mixed integer linear programming")
  Member "robustness of information diffusion algorithms to locally bounded adversaries":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "inner attention supported adaptive cooperation for heterogeneous multi robots teaming based on multi agent reinforcement learning")

Question: Please tell me which class the source paper 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)