ENHANCING SUSTAINABILITY IN WIRELESS SENSOR NETWORKS THROUGH PSO-BASED CLUSTER OPTIMIZATION AND ADAPTIVE SINK MOBILITY
Wireless Sensor Networks (WSNs) represent a fundamental part of current Internet of Things (IoT) systems, allowing for constant monitoring in smart cities, the environment, and industrial systems. However, a fundamental limitation of these networks over long-term operation is uneven energy consumption and the energy-hole problem that arises around a static sink. To address these issues, this paper presents PSO-MSM, a sustainability-oriented communication protocol that combines multi-objective Particle Swarm Optimization (PSO) and adaptive mobile sink mobility. The protocol optimizes cluster head (CH) selection and dynamically adjusts the sink’s trajectory through multi-radius circular paths to balance the forwarding load across the sensing field. Optimization is performed jointly with consideration of residual energy, intra-cluster compactness, and the proximity of each CH to the sink. This coordinated clustering-mobility design reduces long-distance transmissions, relieves hotspot depletion, and improves overall energy sustainability. Extensive ns-3 simulations demonstrate that PSO-MSM significantly enhances network lifetime, increasing the time to first-node-dead, half-nodes-dead, and last-node-dead events by 46% compared with LEACH, HEED, and PEGASIS. The protocol also achieves higher residual energy, improved packet delivery ratio, reduced end-to-end delay, decreased channel congestion, and significantly lower energy imbalance. These results indicate that PSO-MSM provides an effective solution for smart city and IoT deployments, offering reliability, reduced maintenance, and improved sustainability for long-term operations where these issues are a major priority.
Authors
- Bandar Altubaishe
- Ghassan Samara (ORCID: https://orcid.org/0000-0001-8415-0572)
- Mehmet Kemal Özdemir (ORCID: https://orcid.org/0000-0002-9054-0005)
- Mohammed M. Aman (ORCID: https://orcid.org/0000-0002-9064-9596)
- Hasan Al-Refai
- Eyad A. Shaban
- Mahmoud Odeh
Institutions
- Al-Ahliyya Amman University (JO)
- Zarqa University (JO)
- American University of Madaba (JO)
- Istanbul Medipol University (TR)
- University of Business and Technology (SA)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-01-05
- DOI
- https://doi.org/10.5281/zenodo.18156706
- Primary Topic
- Energy Efficient Wireless Sensor Networks
- Type
- article
- Field-Weighted Citation Impact
- 0.00