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Reliably Detecting Connectivity using Local Graph Traits

dc.date.accessioned2010-09-11T00:00:21Z
dc.date.accessioned2018-11-26T22:26:24Z
dc.date.available2010-09-11T00:00:21Z
dc.date.available2018-11-26T22:26:24Z
dc.date.issued2010-09-09
dc.identifier.urihttp://hdl.handle.net/1721.1/58484
dc.identifier.urihttp://repository.aust.edu.ng/xmlui/handle/1721.1/58484
dc.description.abstractLocal distributed algorithms can only gather sufficient information to identify local graph traits, that is, properties that hold within the local neighborhood of each node. However, it is frequently the case that global graph properties (connectivity, diameter, girth, etc) have a large influence on the execution of a distributed algorithm. This paper studies local graph traits and their relationship with global graph properties. Specifically, we focus on graph k-connectivity. First we prove a negative result that shows there does not exist a local graph trait which perfectly captures graph k-connectivity. We then present three different local graph traits which can be used to reliably predict the k-connectivity of a graph with varying degrees of accuracy. As a simple application of these results, we present upper and lower bounds for a local distributed algorithm which determines if a graph is k-connected. As a more elaborate application of local graph traits, we describe, and prove the correctness of, a local distributed algorithm that preserves k-connectivity in mobile ad hoc networks while allowing nodes to move independently whenever possible.en_US
dc.format.extent16 pen_US
dc.subjectConnectivityen_US
dc.subjectGraph Traitsen_US
dc.subjectDistributeden_US
dc.titleReliably Detecting Connectivity using Local Graph Traitsen_US


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