Soluções cientes de agregação de dados da correlação espaço-temporal e consumo de energia para realizar coleta de dados em redes de sensores sem fio

Abstract

This work provides a general discussion for data aggregation and exploiting spatio-temporal data correlation in wireless sensor networks(WSNs), allowing us to identify open issues and understand the requirements and the implications regarding data aggregation, and exploiting spatio-temporal data correlation in WSNs.In this discussion, we survey the state-of-the-art about data aggregation and spatio-temporal data correlation in WSNs. By assessing the architectures, models, and methods of data aggregation and spatio-temporal data correlation identified in the survey, we propose four different solutions for the data aggregation and exploiting spatio-temporal data correlation problems that are suitable for different senarios in WSNs. These proposed solutions are called the DAARP, DDAARP, DST e EAST. The proposed algorithms reduce the number of message necessary to set up a routing tree, maximizes the number of overlapping routes, select routes with the highest aggregation rate, and performs reliable data aggregation transmission.The proposed solutions have been widely compared with other solutions in the literature and the results show that the proposed solutions may be a potential alternative to perform data aggregation and exploit spatio-temporal data correlation during routing. We also present an extensive set of experiments to evaluate the performance of our algorithms. Our results indicate that our proposed solutions are suitable for implementation in WSNs.