Interaction Maxima in Distributed Systems

TL;DR

This paper investigates the maximum possible interaction in distributed systems modeled as graphs, identifying optimal data distributions for various graph structures and extending classical mathematical results to this context.

Contribution

It introduces a model for maximum interaction in distributed systems and characterizes optimal data distributions for different graph types, extending Motzkin and Straus's classical result.

Findings

Maximum interaction occurs with data concentrated in a pair of neighbors for bipartite graphs.

Equal load partitioning is optimal in complete graphs.

In general graphs, data should be evenly distributed in the largest clique.

Abstract

In this paper we study the maximum degree of interaction which may emerge in distributed systems. It is assumed that a distributed system is represented by a graph of nodes interacting over edges. Each node has some amount of data. The intensity of interaction over an edge is proportional to the product of the amounts of data in each node at either end of the edge. The maximum sum of interactions over the edges is searched for. This model can be extended to other interacting entities. For bipartite graphs and odd-length cycles we prove that the greatest degree of interaction emerge when the whole data is concentrated in an arbitrary pair of neighbors. Equal partitioning of the load is shown to be optimum for complete graphs. Finally, we show that in general graphs for maximum interaction the data should be distributed equally between the nodes of the largest clique in the graph. We also present in this context a result of Motzkin and Straus from 1965 for the maximal interaction objective.