http://dx.doi.org/10.1016/j.jnca.2014.09.013 URL
http://www.sciencedirect.com/science/article/pii/S1084804514002203
http://www.scopus.com/inward/record.url?eid=2-s2.0-84908450433&partnerID=40&md5=22107cf1d2a72082a59f31745b0f37e5
Keywords
Lossless compression; Wireless Sensor Networks Abstract
Compression algorithms are deeply used in Wireless Sensor Networks (WSNs) for data aggregation in order to reduce energy consumption and therefore increasing network lifetime. In this paper we compare several lossless compression algorithms by means of real-world data. Moreover we present a simple and effective lossless compression algorithm that is able to outperform existing solutions and that, considering its inherent low complexity and memory requirements, is well suited for WSNs.
http://dx.doi.org/10.1109/ICCEP.2015.7177583 URL
http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7177583
http://www.scopus.com/inward/record.url?eid=2-s2.0-84946542317&partnerID=40&md5=16052cf0838d1ca3aca33ca53c8eca02
Keywords
maximum power point trackers; photovoltaic power systems; power system simulation; sunlight; synchronisation; wireless sensor networks; MIC PV plants; Matlab-Simulink; PV generator; PV module electric variables; WSN; centralized MPPT system; data losses; efficiency assessment; module integrated converter; power generator;solar irradiation; wireless data transfer network ;wireless sensor networks; Microwave integrated circuits; Radiation effects; Software packages; Temperature measurement; Temperature sensors; Wireless communication; Wireless sensor networks;.Maximum Power Point Tracking; Module Integrated Converter; Photovoltaic systems; Wireless Sensor Network Abstract
The paper describes a simulation framework able to accomplish a simulation of a PV plants including a Wireless Sensor Network (WSN). The developed framework is entirely implemented in a Matlab/Simulink environment, and can be used to accomplish in-depth performance evaluation of two very different systems interacting between them, the power generator and the wireless data transfer network. As an example, the developed framework is exploited to investigate the effects of possible data losses, or delays, on the efficiency of a PV generator based on the Module Integrated Converter concept and equipped with a centralized MPPT system exploiting a WSN to monitor PV modules electric variables and the distribution of solar irradiation and temperature over the plant area.
http://dx.doi.org/10.1155/2016/4156358 URL
http://www.hindawi.com/journals/ijdsn/2016/4156358/ Abstract
We study the problem of data gathering in wireless sensor networks and compare several approaches belonging to different research fields; in particular, signal processing, compressive sensing, information theory, and networking related data gathering techniques are investigated. Specifically, we derived a simple analytical model able to predict the energy efficiency and reliability of different data gathering techniques.Moreover, we carry out simulations to validate our model and to compare the effectiveness of the above schemes by systematically sampling the parameter space (i.e., number of nodes, transmission range, and sparsity). Our simulation and analytical results show that there is no best data gathering technique for all possible applications and that the trade-off between energy consumptions and reliability could drive the choice of the data gathering technique to be used. In this context, our model could be a useful tool.