We study local aggregation and graph analysis in distributed environments using the message passing model. We provide a flexible framework, where each of the nodes in a set S--which is a subset of all nodes in the network--can perform a large range of common aggregation functions in its k-neighborhood. We study this problem in the CONGEST model, where in each synchronous round, every node can transmit a different (but short) message to each of its neighbors. While the k-neighborhoods of nodes in S might overlap and aggregation could cause congestion in this model, we present an algorithm that needs time O(∣S∣+k) even when each of the nodes in S performs a different aggregation on its k-neighborhood. The framework is not restricted to aggregation-trees such that it can be used for more advanced graph analysis. We demonstrate this by providing efficient approximations of centrality measures and approximation of minimum routing cost trees.
@article{arxiv.1605.06882,
title = {Distributed Local Multi-Aggregation and Centrality Approximation},
author = {Benjamin Dissler and Stephan Holzer and Roger Wattenhofer},
journal= {arXiv preprint arXiv:1605.06882},
year = {2016}
}