AEETMS: An Attribute-Based Energy Efficient Scheduling Scheme for Enhanced Performance and Longevity in Wireless Sensor Networks.

Saved in:

Bibliographic Details
Title:	AEETMS: An Attribute-Based Energy Efficient Scheduling Scheme for Enhanced Performance and Longevity in Wireless Sensor Networks.
Authors:	N., Khadirkumar¹ khadir_n@myyahoo.com, A., Bharathi² bharathia@bitsathy.ac.in
Source:	Technical Gazette / Tehnički Vjesnik. Oct2025, Vol. 32 Issue 5, p1723-1728. 6p.
Subjects:	Wireless sensor networks, Energy consumption, Scheduling, Network performance, Acquisition of data, Bandwidths
Abstract:	Wireless Sensor Networks (WSNs) are gaining increasing popularity due to their ability to provide comprehensive coverage through sensor nodes that span across an entire infrastructure. These networks are widely employed in military applications, where node mobility and recovery are critical for tasks such as program searching and data prioritization. The performance of WSNs heavily depends on the adoption of efficient scheduling techniques to address energy constraints and communication challenges. In this context, we propose an Attribute-based Energy Efficient Traffic Minimization Scheduling (AEETMS) scheme to enhance network performance and extend its lifetime. Our approach begins by estimating the initial energy of nodes before scheduling transmission channels, thereby improving network longevity. The network topology is first transformed into a mixed graph model, which helps to reduce interference and energy consumption among communication nodes through multitasking table techniques. Next, the initial scheduling is performed using Energy-Aware Data Aggregation (EADA). Unused nodes are efficiently identified and managed to conserve energy and minimize time complexity. The proposed method estimates the Packet Loss Rate (PLR) at each node, prioritizing packet transmission based on importance. High-priority packets are allocated time slots and transmitted continuously, superseding lower-priority data packets. To further optimize data aggregation, selecting an appropriate parent node for packet transmission is crucial. Once data aggregation is optimized, nodes transmit fewer packets, significantly reducing energy consumption. Performance metrics such as energy consumption, throughput, and delivery ratio are analyzed to evaluate the effectiveness of the AEETMS scheme. Comparisons with existing methods demonstrate that AEETMS outperforms them in terms of energy efficiency and network throughput. [ABSTRACT FROM AUTHOR]
	Copyright of Technical Gazette / Tehnički Vjesnik is the property of Tehnicki Vjesnik and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database:	Engineering Source

Description
Abstract:	Wireless Sensor Networks (WSNs) are gaining increasing popularity due to their ability to provide comprehensive coverage through sensor nodes that span across an entire infrastructure. These networks are widely employed in military applications, where node mobility and recovery are critical for tasks such as program searching and data prioritization. The performance of WSNs heavily depends on the adoption of efficient scheduling techniques to address energy constraints and communication challenges. In this context, we propose an Attribute-based Energy Efficient Traffic Minimization Scheduling (AEETMS) scheme to enhance network performance and extend its lifetime. Our approach begins by estimating the initial energy of nodes before scheduling transmission channels, thereby improving network longevity. The network topology is first transformed into a mixed graph model, which helps to reduce interference and energy consumption among communication nodes through multitasking table techniques. Next, the initial scheduling is performed using Energy-Aware Data Aggregation (EADA). Unused nodes are efficiently identified and managed to conserve energy and minimize time complexity. The proposed method estimates the Packet Loss Rate (PLR) at each node, prioritizing packet transmission based on importance. High-priority packets are allocated time slots and transmitted continuously, superseding lower-priority data packets. To further optimize data aggregation, selecting an appropriate parent node for packet transmission is crucial. Once data aggregation is optimized, nodes transmit fewer packets, significantly reducing energy consumption. Performance metrics such as energy consumption, throughput, and delivery ratio are analyzed to evaluate the effectiveness of the AEETMS scheme. Comparisons with existing methods demonstrate that AEETMS outperforms them in terms of energy efficiency and network throughput. [ABSTRACT FROM AUTHOR]
ISSN:	13303651
DOI:	10.17559/TV-20241113002126