A novel mobile sink placement in wireless sensor network using deep maxout network based energy prediction with adjacent cell score
- Title
- A novel mobile sink placement in wireless sensor network using deep maxout network based energy prediction with adjacent cell score
- Creator
- Nisha, U. Nilabar; Manikandan, A.; Venkataramanan, C.; Ashok, J.
- Description
- The majority of Wireless Sensor Networks (WSNs) are made up of energy- and cost-efficient detecting nodes. Traditional wireless sensor networks encounter serious problems, including latency, network failure, and congestion, since they rely on individual base stations (BSs) to gather data from the whole network. Sensor nodes adjacent to the base station will use more energy because of excessive energy consumption and energy-hole constraints, affecting the network's life. Understanding the best place for mobile sink nodes can help alleviate this issue by lowering energy usage and extending the network's lifespan. In this paper, utilizing a deep learning-based energy prediction and neighbour cell score model, we build and construct an efficient method to locate mobile receivers using distance, expected energy, and fairness variables. Furthermore, a Deep Maximum Output Network (DMN) calculates the desired power. However, the minimum length, maximum residual energy, complete normalized right, maximum network lifespan, and maximum normalized throughput for our suggested neighbor-based cell scoring with Deep Maxout Network are 137.364, 30.903, 64.426, and 60.613, respectively. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.
- Source
- Wireless Networks;Volume;31;Issue;8;pp.4823-4838
- Date
- 01-01-2025
- Publisher
- Springer
- Subject
- Cluster head (CH); Deep maxout networks; Mobile aggregation nodes; Voronoi partition; Wireless sensor networks (WSN)
- Coverage
- Nisha U.N., Department of CSE, Mahendra Institute of Technology, Mallasamudram, India; Manikandan A., Department of ECE, SRM Institute of Science and Technology, Kattankulathur, 603203, India; Venkataramanan C., Department of ECE, Sri Eshwar College of Engineering, Tamil Nadu, Coimbatore, 641202, India; Ashok J., School of Business and Management, CHRIST (Deemed to be University), Karnataka, Bengaluru, India
- Rights
- Restricted Access; Hardcopy may be available in the library
- Relation
- ISSN: 10220038; CODEN: WINEF
- Format
- online
- Language
- English
- Type
- Article
Collection
Citation
Nisha, U. Nilabar; Manikandan, A.; Venkataramanan, C.; Ashok, J., “A novel mobile sink placement in wireless sensor network using deep maxout network based energy prediction with adjacent cell score,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/21964.