Latency, Capacity, and Distributed MST
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Consider the problem of building a minimum-weight spanning tree for a given graph G. In this paper, we study the cost of distributed MST construction where each edge has a latency and a capacity, along with the weight. Edge latencies capture the delay on the links of the communication network, while capacity captures their throughput (in this case the rate at which messages can be sent). Depending on how the edge latencies relate to the edge weights, we provide several tight bounds on the time required to construct an MST. When there is no correlation between the latencies and the weights, we show that (unlike the sub-linear time algorithms in the standard CONGEST model, on small diameter graphs), the best time complexity that can be achieved is Θ̃(D+n/c), where edges have capacity c and D refers to the latency diameter of the graph. However, if we restrict all edges to have equal latency ℓ and capacity c, we give an algorithm that constructs an MST in Õ(D + √(nℓ/c)) time. Next, we consider the case where latencies are exactly equal to the weights. Here we show that, perhaps surprisingly, the bottleneck parameter in determining the running time of an algorithm is the total weight W of the constructed MST by showing a tight bound of Θ̃(D + √(W/c)). In each case, we provide matching lower bounds.
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