Tight Analysis of Asynchronous Rumor Spreading in Dynamic Networks

05/16/2020

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by   Ali Pourmiri, et al.

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The asynchronous rumor algorithm spreading propagates a piece of information, the so-called rumor, in a network. Starting with a single informed node, each node is associated with an exponential time clock with rate 1 and calls a random neighbor in order to possibly exchange the rumor. Spread time is the first time when all nodes of a network are informed with high probability. We consider spread time of the algorithm in any dynamic evolving network, 𝒢={G^(t)}_t=0^∞, which is a sequence of graphs exposed at discrete time step t=0,1.... We observe that besides the expansion profile of a dynamic network, the degree distribution of nodes over time effect the spread time. We establish upper bounds for the spread time in terms of graph conductance and diligence. For a given connected simple graph G=(V,E), the diligence of cut set E(S, S) is defined as ρ(S)=min_{u,v}∈ E(S,S)max{d̅/d_u, d̅/d_v} where d_u is the degree of u and d̅ is the average degree of nodes in the one side of the cut with smaller volume (i.e., 𝚟𝚘𝚕(S)=∑_u∈ Sd_u). The diligence of G is also defined as ρ(G)=min_∅≠ S⊂ Vρ(S). We show that the spread time of the algorithm in 𝒢 is bounded by T, where T is the first time that ∑_t=0^TΦ(G^(t))·ρ(G^(t)) exceeds Clog n, where Φ(G^(t)) denotes the conductance of G^(t) and C is a specified constant. We also define the absolute diligence as ρ(G)=min_{u,v}∈ Emax{1/d_u,1/d_v} and establish upper bound T for the spread time in terms of absolute diligence, which is the first time when ∑_t=0^T⌈Φ(G^(t))⌉·ρ(G^(t))> 2n. We present dynamic networks where the given upper bounds are almost tight.