Please use this identifier to cite or link to this item: http://repositorio.inesctec.pt/handle/123456789/4115
Title: Flow updating: Fault-tolerant aggregation for dynamic networks
Authors: Jesus,P
Carlos Baquero
Paulo Sérgio Almeida
Issue Date: 2015
Abstract: Data aggregation is a fundamental building block of modern distributed systems. Averaging based approaches, commonly designated gossip-based, are an important class of aggregation algorithms as they allow all nodes to produce a result, converge to any required accuracy, and work independently from the network topology. However, existing approaches exhibit many dependability issues when used in faulty and dynamic environments. This paper describes and evaluates a fault tolerant distributed aggregation technique, Flow Updating, which overcomes the problems in previous averaging approaches and is able to operate on faulty dynamic networks. Experimental results show that this novel approach outperforms previous averaging algorithms; it self-adapts to churn and input value changes without requiring any periodic restart, supporting node crashes and high levels of message loss, and works in asynchronous networks. Realistic concerns have been taken into account in evaluating Flow Updating, like the use of unreliable failure detectors and asynchrony, targeting its application to realistic environments.
URI: http://repositorio.inesctec.pt/handle/123456789/4115
http://dx.doi.org/10.1016/j.jpdc.2015.02.003
metadata.dc.type: article
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Appears in Collections:HASLab - Articles in International Journals

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