Scipediacontent: Scipediacontent moved page Draft Content 641198945 to Esposito et al 2017a

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Scipediacontent moved page Draft Content 641198945 to Esposito et al 2017a

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Created page with " == Abstract == Gossiping is a widely known and successful approach to reliable communications, tolerating packet losses and link crashes. It has been extensively used in sev..."

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== Abstract ==

Gossiping is a widely known and successful approach to reliable communications, tolerating packet losses and link crashes. It has been extensively used in several middleware kinds, such as event notification services and application domains, like infrastructures for air traffic management, power grid control, health information exchange, just to cite some of them. Despite achieving a high loss-tolerance and scalability degrees, gossiping is affected by degraded performances and heavy traffic loads on the network. For this reason, it may be not optimal in applications where reliability must be provided jointly with timeliness and/or in congestion-prone networks. The crucial aspect for improving a gossiping scheme is deciding which nodes should receive a gossiping message, and our driving idea is to adopt a distributed strategic learning logic to determine such nodes in an efficient manner. This is able to resolve gossiping's weakness points and to achieve better performance and reduced traffic loads. This paper describes how to introduced strategic learning in a gossip scheme so as to determine the best set of nodes that can be used to send gossip messages and to optimize their utility. Such a solution has been experimentally assessed through a set of simulations demonstrating the effectiveness of the proposal.

== Original document ==

The different versions of the original document can be found in:

* [http://hdl.handle.net/11591/373289 http://hdl.handle.net/11591/373289]

* [https://api.elsevier.com/content/article/PII:S0167739X16305520?httpAccept=text/xml https://api.elsevier.com/content/article/PII:S0167739X16305520?httpAccept=text/xml],
: [https://api.elsevier.com/content/article/PII:S0167739X16305520?httpAccept=text/plain https://api.elsevier.com/content/article/PII:S0167739X16305520?httpAccept=text/plain],
: [http://dx.doi.org/10.1016/j.future.2016.11.006 http://dx.doi.org/10.1016/j.future.2016.11.006] under the license https://www.elsevier.com/tdm/userlicense/1.0/

* [https://dblp.uni-trier.de/db/journals/fgcs/fgcs71.html#EspositoCPF17 https://dblp.uni-trier.de/db/journals/fgcs/fgcs71.html#EspositoCPF17],
: [https://www.sciencedirect.com/science/article/pii/S0167739X16305520 https://www.sciencedirect.com/science/article/pii/S0167739X16305520],
: [https://doi.org/10.1016/j.future.2016.11.006 https://doi.org/10.1016/j.future.2016.11.006],
: [https://core.ac.uk/display/84072158 https://core.ac.uk/display/84072158],
: [https://academic.microsoft.com/#/detail/2553066228 https://academic.microsoft.com/#/detail/2553066228]

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Esposito et al 2017a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 641198945 to Esposito et al 2017a

Scipediacontent: Created page with " == Abstract == Gossiping is a widely known and successful approach to reliable communications, tolerating packet losses and link crashes. It has been extensively used in sev..."