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 "on the role of mobility for multimessage gossip"):
  Abstract: We consider information dissemination in a large n -user wireless network in which k users wish to share a unique message with all other users. Each of the n users only has knowledge of its own contents and state information; this corresponds to a one-sided push-only scenario. The goal is to disseminate all messages efficiently, hopefully achieving an order-optimal spreading rate over unicast wireless random networks. First, we show that a random-push strategy-where a user sends its own or a received packet at random-is order-wise suboptimal in a random geometric graph: specifically, Ω(√n) times slower than optimal spreading. It is known that this gap can be closed if each user has “full” mobility, since this effectively creates a complete graph. We instead consider velocity-constrained mobility where at each time slot the user moves locally using a discrete random walk with velocity v(n) that is much lower than full mobility. We propose a simple two-stage dissemination strategy that alternates between individual message flooding (“self promotion”) and random gossiping. We prove that this scheme achieves a close to optimal spreading rate (within only a logarithmic gap) as long as the velocity is at least v(n)=ω(√(logn/k)). The key insight is that the mixing property introduced by the partial mobility helps users to spread in space within a relatively short period compared to the optimal spreading time, which macroscopically mimics message dissemination over a complete graph.

Includes members:
  Member "information spreading in dynamic graphs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "relative hausdorff distance for network analysis")
  Member "tight bounds on information dissemination in sparse mobile networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "improved bounds on information dissemination by manhattan random waypoint model")
  Member "information spreading in stationary markovian evolving graphs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "how fast can we reach a target vertex in stochastic temporal graphs")
  Member "analyzing network coding gossip made easy":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "synchronous transmissions in low power wireless a survey of communication protocols and network services")
  Member "distributed averaging via lifted markov chains":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "consensus over random graph processes network borel cantelli lemmas for almost sure convergence")
  Member "the impact of mobility on gossip algorithms":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "sample greedy gossip distributed kalman filter")
  Member "gossiping with multiple messages":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "stability and scalability of blockchain systems")
  Member "fast distributed algorithms for computing separable functions":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "distributed voting in beep model")

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.SI(Social and Information Networks)