<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="6.x">Drupal-Biblio</source-app><ref-type>47</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Francisco Maia</style></author><author><style face="normal" font="default" size="100%">Miguel Matos</style></author><author><style face="normal" font="default" size="100%">Ricardo Vilaça</style></author><author><style face="normal" font="default" size="100%">José Orlando Pereira</style></author><author><style face="normal" font="default" size="100%">Rui Oliveira</style></author><author><style face="normal" font="default" size="100%">Etienne Rivière</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">DATAFLASKS: epidemic store for massive scale systems</style></title><secondary-title><style face="normal" font="default" size="100%">The 33rd IEEE Symposium on Reliable Distributed Systems (SRDS 2014) </style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2014</style></year><pub-dates><date><style  face="normal" font="default" size="100%">October</style></date></pub-dates></dates><urls><related-urls><url><style face="normal" font="default" size="100%">https://haslab.uminho.pt/sites/default/files/mmatos/files/main.pdf</style></url></related-urls></urls><pub-location><style face="normal" font="default" size="100%">Nara, Japan</style></pub-location><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Very large scale distributed systems provide some of the most interesting research challenges while at the same time being increasingly required by nowadays applications. The escalation in the amount of connected devices and data being produced and exchanged, demands new data management systems. Although new data stores are continuously being proposed, they are not suitable for very large scale environments. The high levels of churn and constant dynamics found in very large scale systems demand robust, proactive and unstructured approaches to data management. In this paper we propose a novel data store solely based on epidemic (or gossip-based) protocols. It leverages the capacity of these protocols to provide data persistence guarantees even in highly dynamic, massive scale systems. We provide an open source prototype of the data store and correspondent evaluation.&lt;/p&gt;
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