Title: Important extrema points extraction-based data aggregation approach for elongating the WSN lifetime

Authors: Ali Kadhum M. Al-Qurabat; Hussein M. Salman; Abd Alnasir Riyadh Finjan

Addresses: Department of Computer Science, College of Science for Women, University of Babylon, Babylon, Iraq ' Department of Polymer Engineering and Petrochemical Industries, College of Material Engineering, University of Babylon, Babylon, Iraq ' Supreme Commission for Hajj and Umrah, Baghdad, Iraq

Abstract: Energy conservation is one of the most basic problems of wireless sensor networks. Energy of sensor nodes is limited, so effective energy usage is important. Data aggregation helps to minimise the volume of data communicated across the network while preserving information quality and decreasing energy waste, thereby enhancing the lifetime of network. In this paper, we propose a data aggregation approach based on the important extrema points extraction for elongating the WSN lifetime (IEEDA). Rather than transmitting all the set of collected measures at the end of every time period, we propose transmitting the extracted important extrema measures of sensor node. Using real-world data sets with radically different properties, we tested our method against two protocols ATP and PFF. The proposed method resulted in a reduction in the amount of the following: data remaining up to 95%, data sent up to 80%, and energy consumed up to 77%.

Keywords: data aggregation; important extrema points; lifetime; WSN.

DOI: 10.1504/IJCAT.2022.125182

International Journal of Computer Applications in Technology, 2022 Vol.68 No.4, pp.357 - 368

Received: 30 May 2021
Accepted: 07 Jul 2021

Published online: 01 Sep 2022 *

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