文章基本信息

标题：Performance of Data Reduction Algorithms for Wireless Sensor Network (WSN) using Different Real-Time Datasets: Analysis Study
本地全文：下载
作者：M. K. Hussein ; Ion Marghescu ; Nayef.A.M. Alduais 等
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2022
卷号：13
期号：1
DOI：10.14569/IJACSA.2022.0130178
语种：English
出版社：Science and Information Society (SAI)
摘要：This paper investigates the effect of data reduction methods in the performance of Wireless Sensor Network (WSN) using a variety of real-time datasets. The simulation tests are carried out in MATLAB for several methods of reducing the quantity of sent data. These approaches are Data Reduction based - Neural Network Fitting (NNF), Neural Network Time Series (NNTS), Linear Regression with Multiple Variables (LRMV), Data Reduction based – “An Efficient Data Collection and Dissemination (EDCD2)” and Data Reduction based – Fast Independent Component Analysis (FICA). The selected algorithms NNF, NNST, EDCD2, LRMV, and FICA are evaluated using real-time datasets. The performance indicators included are energy consumption, data accuracy, and data reduction percentage. The research results show that the selected algorithm helps to reduce the amount of data transferred and consumed energy, but each algorithm performs differently depending on the dataset used.
关键词：Data reduction algorithms; WSN; energy consumption; accuracy; neural network; independent component analysis