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JAIT 2023 Vol.14(1): 112-121
doi: 10.12720/jait.14.1.112-121

Energy Prediction for Mobile Sink Placement by Deep Maxout Network in WSN

Chamandeep Kaur 1,*, Samar Mansour Hassen 2, Mawahib Sharafeldin Adam Boush 3, and Harishchander Anandaram 4
1. Computer Science & Information Technology Department, Jazan University, Jizan, Saudi Arabia
2. Department of Management Information Systems, Jazan University, Jizan, Saudi Arabia
3. Computer Science Department, Jazan University, Jizan, Saudia Arabia
4. Centre for Excellence in Computational Engineering and Networking, Amrita Vishwa Vidyapeetham, Coimbatore, Tamil Nadu, India
*Correspondence: kaur.chaman83@gmail.com

Manuscript received July 2, 2022; revised August 29, 2022; accepted September 13, 2022; published February 17, 2023.

Abstract—In a Wireless Sensor Network (WSN), Numerous cost-effective and energy-constrained sensor nodes are typically used. In a typical Wireless Sensor Network, a single Base Station (BS) gathers information from the whole network, which contributes to concerns including latency, network failure, and congestion. The overwhelming proportion of energy consumption, as well as the energy hole limitation, significantly degrades the overall system performance and network lifetime, which is owing to the sensor nodes that are near the BS consuming more energy. To tackle this problem, it’s essential to determine the perfect spot for mobile sink nodes, which minimizes the power consumed and so increases the network's lifespan. In this work, an effective strategy is designed and developed to detect the location of a mobile sink considering factors such as distance, estimated energy, and fairness, using Deep learning-based energy prediction with an adjacency cell score model. In addition, the predicted energy is determined by employing the Deep Maxout Network (DMN). However, a Minimum distance of 137.364, maximal residual energy of 30.903, maximum standardized fairness of 64.426, maximum network duration of 60, and maximum standardized throughput of 60.613 was obtained using the proposed adjacency-based cell score + Deep Maxout Network.
 
Keywords—Wireless Sensor Network (WSN), mobile sink nodes, deep Maxout network, Base Station (BS) and energy prediction

Cite: Chamandeep Kaur, Samar Mansour Hassen, Mawahib Sharafeldin Adam Boush, and Harishchander Anandaram, "Energy Prediction for Mobile Sink Placement by Deep Maxout Network in WSN," Journal of Advances in Information Technology, Vol. 14, No. 1, pp. 112-121, February 2023.

Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.

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