Dense Subgraphs on Dynamic Networks

Atish Das Sarma, Ashwin Lall, Danupon Nanongkai, and Amitabh Trehan

Abstract
In distributed networks, it is often useful for the nodes to be aware of dense subgraphs, e.g., such a dense subgraph could reveal dense substructures in otherwise sparse graphs (e.g. the World Wide Web or social networks); these might reveal community clusters or dense regions for possibly maintaining good communication infrastructure. In this work, we address the problem of self-awareness of nodes in a dynamic network with regards to graph density, i.e., we give distributed algorithms for maintaining dense subgraphs that the member nodes are aware of. The only knowledge that the nodes need is that of the dynamic diameter , i.e., the maximum number of rounds it takes for a message to traverse the dynamic network. For our work, we consider a model where the number of nodes are fixed, but a powerful adversary can add or remove a limited number of edges from the network at each time step. The communication is by broadcast only and follows the CONGEST model. Our algorithms are continuously executed on the network, and at any time (after some initialization) each node will be aware if it is part (or not) of a particular dense subgraph. We give algorithms that -approximate the densest subgraph and -approximate the at-least-k-densest subgraph (for a given parameter k). Our algorithms work for a wide range of parameter values and run in time. Further, a special case of our results also gives the first fully decentralized approximation algorithms for densest and at-least-k-densest subgraph problems for static distributed graphs.

 

Guest: Amitabh Trehan
Host: Shantanu Das

“Tri, Tri again”: Finding Triangles and Small Subgraphs in a Distributed Setting

Danny Dolev, Christoph Lenzen, and Shir Peled

Abstract:
Let be an n-vertex graph and a d-vertex graph, for some constant d. Is a subgraph of G? We consider this problem in a model where all n processes are connected to all other processes, and each message contains up to bits. A simple deterministic algorithm that requires communication rounds is presented. For the special case that is a triangle, we present a probabilistic algorithm that requires an expected rounds of communication, where t is the number of triangles in the graph, and with high probability. We also present deterministic algorithms specially suited for sparse graphs.

Guest: Christoph Lenzen
Host: Shantanu Das