<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Sabrina Boubiche</style></author><author><style face="normal" font="default" size="100%">Boubiche, Djallel-Eddine</style></author><author><style face="normal" font="default" size="100%">Azzedine Bilami</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Integrating Big data paradigm in WSNs</style></title><secondary-title><style face="normal" font="default" size="100%"> International Conference on Big Data and Advanced Wireless Technologies</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2016</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2016</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://dl.acm.org/doi/abs/10.1145/3010089.3017606</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">WSNs consist of large number of small sensors densely deployed to monitor a phenomenon. Most of the data generated from the WSNs represent events happening at time intervals. Sometimes and according to the nature of the applications, this data stream is continuous and can reach high speeds. Therefore, adopting new techniques, platforms and tools to deal with this large amount of sensory data became necessary. Therefore, the Big Data paradigm can represent a good solution for the extraction, analysis, viewing, sharing, storage and transfer of such volume of data. This paper presents a survey on integrating Big Data tools for gathering, storing and analyzing the data generated by WSNs.</style></abstract></record></records></xml>