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 gathering in networks"):
  Abstract: This paper investigates an open problem introduced in [14]. Two or more mobile agents start from different nodes of a network and have to accomplish the task of gathering which consists in getting all together at the same node at the same time. An adversary chooses the initial nodes of the agents and assigns a different positive integer (called label) to each of them. Initially, each agent knows its label but does not know the labels of the other agents or their positions relative to its own. Agents move in synchronous rounds and can communicate with each other only when located at the same node. Up to f of the agents are Byzantine. A Byzantine agent can choose an arbitrary port when it moves, can convey arbitrary information to other agents and can change its label in every round, in particular by forging the label of another agent or by creating a completely new one. #R##N#What is the minimum number M of good agents that guarantees deterministic gathering of all of them, with termination? #R##N#We provide exact answers to this open problem by considering the case when the agents initially know the size of the network and the case when they do not. In the former case, we prove M=f+1 while in the latter, we prove M=f+2. More precisely, for networks of known size, we design a deterministic algorithm gathering all good agents in any network provided that the number of good agents is at least f+1. For networks of unknown size, we also design a deterministic algorithm ensuring the gathering of all good agents in any network but provided that the number of good agents is at least f+2. Both of our algorithms are optimal in terms of required number of good agents, as each of them perfectly matches the respective lower bound on M shown in [14], which is of f+1 when the size of the network is known and of f+2 when it is unknown.

Includes members:
  Member "time versus cost tradeoffs for deterministic rendezvous in networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "byzantine gathering in polynomial time")
  Member "rendezvous of distance aware mobile agents in unknown graphs":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "deterministic meeting of sniffing agents in the plane")
  Member "fast rendezvous with advice":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "asynchronous approach in the plane a deterministic polynomial algorithm")
  Member "how to meet asynchronously at polynomial cost":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "want to gather no need to chatter")
  Member "delays induce an exponential memory gap for rendezvous in trees":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "want to gather no need to chatter")
  Member "anonymous meeting in networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "want to gather no need to chatter")
  Member "the gathering problem for two oblivious robots with unreliable compasses":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "using model checking to formally verify rendezvous algorithms for robots with lights in euclidean space")
  Member "how to meet asynchronously almost everywhere":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "positional encoding by robots with non rigid movements")

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)