<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Volodymyr Petrivskyi</style></author><author><style face="normal" font="default" size="100%">Georgi Dimitrov</style></author><author><style face="normal" font="default" size="100%">Viktor Shevchenko</style></author><author><style face="normal" font="default" size="100%">Oleksiy Bychkov</style></author><author><style face="normal" font="default" size="100%">Magdalena Garvanova</style></author><author><style face="normal" font="default" size="100%">Galina Panayotova</style></author><author><style face="normal" font="default" size="100%">Pavel Petrov</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Information Technology for Big Data Sensor Networks Stability Estimation</style></title><secondary-title><style face="normal" font="default" size="100%">Information &amp; Security: An International Journal</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">big data</style></keyword><keyword><style  face="normal" font="default" size="100%">coverage radius</style></keyword><keyword><style  face="normal" font="default" size="100%">data loss</style></keyword><keyword><style  face="normal" font="default" size="100%">sensor network</style></keyword><keyword><style  face="normal" font="default" size="100%">sensor network stability</style></keyword><keyword><style  face="normal" font="default" size="100%">sensors</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2020</style></date></pub-dates></dates><volume><style face="normal" font="default" size="100%">47</style></volume><pages><style face="normal" font="default" size="100%">141-154</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">Sensors and sensor networks are widely used in various industries and human activities and main components of the Internet of Things and Industrial Internet of Things concepts. Nowadays, huge amounts of data, called Big Data, can be transported and collected using sensor networks. This article presents approaches for providing sensor networks’ stability estimation for transporting Big Data and collecting respective use cases. The proposed estimation method allows to detect sensor network’s components that decrease data transport system stability. Consequently, additional connections or sensors can be added to increase stability. In the case of data collection, the solution consists of finding the most vulnerable sensor and an optimal position for the additional sensor with given intersection levels with other sensors. Simulation results confirm the feasibility and effectiveness of the proposed approaches.</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue><section><style face="normal" font="default" size="100%">141</style></section></record></records></xml>