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 "analyzing network coding gossip made easy"):
  Abstract: We give a new technique to analyze the stopping time of gossip protocols that are based on random linear network coding (RLNC). Our analysis drastically simplifies, extends and strengthens previous results. We analyze RLNC gossip in a general framework for network and communication models that encompasses and unifies the models used previously in this context. We show, in most settings for the first time, that it converges with high probability in the information-theoretically optimal time. Most stopping times are of the form O(k + T) where k is the number of messages to be distributed and T is the time it takes to disseminate one message. This means RLNC gossip achieves "perfect pipelining". Our analysis directly extends to highly dynamic networks in which the topology can change completely at any time. This remains true even if the network dynamics are controlled by a fully adaptive adversary that knows the complete network state. Virtually nothing besides simple O(kT) sequential flooding protocols was previously known for such a setting. While RLNC gossip works in this wide variety of networks its analysis remains the same and extremely simple. This contrasts with more complex proofs that were put forward to give less strong results for various special cases.

Includes members:
  Member "optimal gossip with direct addressing":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "consensus needs broadcast in noiseless models but can be exponentially easier in the presence of noise")
  Member "broadcast throughput in radio networks routing vs network coding":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "synchronous transmissions in low power wireless a survey of communication protocols and network services")
  Member "tight bounds for rumor spreading with vertex expansion":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the capacity of smartphone peer to peer networks")
  Member "fast structuring of radio networks large for multi message communications":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "broadcasting in noisy radio networks")
  Member "lower bounds on information dissemination in dynamic networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "the communication cost of information spreading in dynamic networks")
  Member "bounded contention coding for wireless networks in the high snr regime":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "cross sender bit mixing coding")
  Member "tighter worst case bounds on algebraic gossip":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "on the influence of graph density on randomized gossiping")
  Member "simple fast and deterministic gossip and rumor spreading":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "network coding gaps for completion times of multiple unicasts")

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)