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 "reaching approximate byzantine consensus with multi hop communication"):
  Abstract: We address the problem of reaching consensus in the presence of Byzantine faults. In particular, we are interested in investigating the impact of messages relay on the network connectivity for a correct iterative approximate Byzantine consensus algorithm to exist. The network is modeled by a simple directed graph. We assume a node can send messages to another node that is up to $l$ hops away via forwarding by the intermediate nodes on the routes, where $l\in \mathbb{N}$ is a natural number. We characterize the necessary and sufficient topological conditions on the network structure. The tight conditions we found are consistent with the tight conditions identified for $l=1$, where only local communication is allowed, and are strictly weaker for $l>1$. Let $l^*$ denote the length of a longest path in the given network. For $l\ge l^*$ and undirected graphs, our conditions hold if and only if $n\ge 3f+1$ and the node-connectivity of the given graph is at least $2f+1$ , where $n$ is the total number of nodes and $f$ is the maximal number of Byzantine nodes; and for $l\ge l^*$ and directed graphs, our conditions is equivalent to the tight condition found for exact Byzantine consensus. #R##N#Our sufficiency is shown by constructing a correct algorithm, wherein the trim function is constructed based on investigating a newly introduced minimal messages cover property. The trim function proposed also works over multi-graphs.

Includes members:
  Member "iterative approximate consensus in the presence of byzantine link failures":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "an improved approximate consensus algorithm in the presence of mobile faults")
  Member "iterative byzantine vector consensus in incomplete graphs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "determining r and r s robustness of digraphs using mixed integer linear programming")
  Member "consensus of multi agent networks in the presence of adversaries using only local information":
    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 "matrix representation of iterative approximate byzantine consensus in directed graphs":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a new approach for distributed hypothesis testing with extensions to byzantine resilience")
  Member "iterative approximate byzantine consensus in arbitrary directed graphs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "grand challenges of resilience autonomous system resilience through design and runtime measures")
  Member "distributed algorithms for consensus and coordination in the presence of packet dropping communication links part ii coefficients of ergodicity analysis approach":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "matrix representation of iterative approximate byzantine consensus in directed graphs")
  Member "robustness of information diffusion algorithms to locally bounded adversaries":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "inner attention supported adaptive cooperation for heterogeneous multi robots teaming based on multi agent reinforcement learning")
  Member "simple gradecast based algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "synchronous byzantine lattice agreement in o log f rounds")

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)