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Energy Minimization in Wireless Sensor Networks Based Bio-Inspired Algorithms

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Artificial Intelligence and Green Computing (ICAIGC 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 806))

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Abstract

The world has witnessed a decrease in computer hardware in recent years, which has given rise to a new generation of computer networks. Wireless sensor networks (WSN) meet the challenges of this new era of computing. The main problem with sensor networks is their power supply, because a sensor has a limited and non-rechargeable energy. And so, this directly influences the life of the sensors and the networks. Energy thus becomes the most important resource of a sensor network. Clustering is a useful method for organizing and extending network life. In this article, we propose a new approach that mixes GWO and ACO, which is used for data routing, and PSO, which allows to create clusters and which is enriched with the k-means algorithm.According to the simulations, the proposed technique demonstrates an improvement compared to other existing techniques in terms of energy consumption, throughput and traffic on the WSN.

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Authors and Affiliations

  1. DATA4EART Laboratory, Faculty of Sciences and Techniques, University Sultan Moulay Slimane, 23000, Beni Mellal, Morocco

    Amal Aabdaoui & Najlae Idrissi

Authors
  1. Amal Aabdaoui
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  2. Najlae Idrissi
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Corresponding author

Correspondence to Amal Aabdaoui .

Editor information

Editors and Affiliations

  1. Data Science for Sustainable Earth Laboratory, Faculty of Sciences and Techniques, Sultan Moulay Slimane University, Beni Mellal, Morocco

    Najlae Idrissi

  2. Data Science for Sustainable Earth Laboratory, Faculty of Sciences and Techniques, Sultan Moulay Slimane University, Beni Mellal, Morocco

    Abdellatif Hair

  3. ENSIAS, Mohammed V University, Rabat, Morocco

    Mohamed Lazaar

  4. Data Science for Sustainable Earth Laboratory, Faculty of Sciences and Techniques, Sultan Moulay Slimane University, Beni Mellal, Morocco

    Youssef Saadi

  5. Data Science for Sustainable Earth Laboratory, Faculty of Sciences and Techniques, Sultan Moulay Slimane University, Beni Mellal, Morocco

    Mohammed Erritali

  6. Faculty of Sciences and Techniques, Hassan First University, Settat, Morocco

    Said El Kafhali

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Aabdaoui, A., Idrissi, N. (2023). Energy Minimization in Wireless Sensor Networks Based Bio-Inspired Algorithms. In: Idrissi, N., Hair, A., Lazaar, M., Saadi, Y., Erritali, M., El Kafhali, S. (eds) Artificial Intelligence and Green Computing. ICAIGC 2023. Lecture Notes in Networks and Systems, vol 806. Springer, Cham. https://doi.org/10.1007/978-3-031-46584-0_14

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