2025/04/07 by William K. Moses Jr., Amanda Redlich, Moses, William K. +3 · 1 voice
Computer Science · #cs.DM
paper · pdf · doi:10.48550/arxiv.2504.05442
We revisit the problem of Broadcast, introduced by Das, Giachoudis, Luccio, and Markou [OPODIS, 2020], where k+1 agents are initially placed on an n node dynamic graph, where 1 agent has a message that must be broadcast to the remaining k ignorant agents. The original paper studied the relationship between the number of agents needed to solve the problem and the edge density of the graph. The paper presented strong evidence that edge density of a graph, or the number of redundant edges within the graph, may be the correct graph property to accurately differentiate whether k= o(n) ignorant agents (low edge density) or k = Ω(n) ignorant agents (high edge density) are needed to solve the problem. In this paper, we show that surprisingly, edge density may not in fact be the correct differentiating property. The original paper presents graphs with edge density 1.16 that require Ω(n) agents, however, we construct graphs with edge density > 1.16 and develop an algorithm to solve the problem on those graphs using only o(n) agents. We subsequently show that the relationship between edge density and number of agents is fairly weak by first constructing graphs with edge density tending to 1 from above that require Ω(n/f(n)) agents to solve, for any function f(n) → ∞ as n → ∞. We then construct an infinite family of graphs with edge density < ρ requiring at least k ignorant agents to solve Broadcast, for any k>1 and ρ>1.