Title: A review of current prediction techniques for extending the lifetime of wireless sensor networks

Authors: Wesal Bassem Nedham; Ali Kadhum M. Al-Qurabat

Addresses: Department of Dentistry, Al-Mustaqbal University College, Babylon, Iraq; Department of Computer Science, University of Babylon, Babylon, Iraq ' Department of Computer Science, College of Science for Women, University of Babylon, Babylon, Iraq

Abstract: The possibility for broad usage of Wireless Sensor Networks (WSNs) in many various sectors, such as environmental monitoring, security, home automation and many others, has increased research interest in WSNs. Although its successes, the broad proliferation of WSNs, especially in distant and inhospitable areas where their usage is most advantageous, is hindered by the primary obstacle of limited energy, as they are often battery operated. To provide these energy-hungry sensor nodes with a longer life expectancy, one technique to achieve this aim is to reduce the frequency of data transfer. Conversely, a portion of the observed data could be predicted to avoid initiating communications that might overwhelm the wireless channel. In this paper, we classify and analyse current prediction-based data reduction strategies for WSNs. Our key contribution is a systematic technique for choosing a prediction model in WSNs based on WSN limitations, prediction technique features and observed data.

Keywords: wireless sensor networks; prediction models; time series models.

DOI: 10.1504/IJCAT.2023.132401

International Journal of Computer Applications in Technology, 2023 Vol.71 No.4, pp.352 - 362

Received: 24 Jun 2022
Received in revised form: 12 Aug 2022
Accepted: 16 Aug 2022
Published online: 19 Jul 2023 *

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