Improving energy efficiency via the use of IoT technologies with intelligent network clustering.
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| Title: | Improving energy efficiency via the use of IoT technologies with intelligent network clustering. |
|---|---|
| Authors: | Abujassar, Radwan S.1 (AUTHOR) r.abujassar@aou.edu.kw, Al-Jarrah, Omar1 (AUTHOR) o.aljarrah@arabou.edu.kw |
| Source: | Wireless Networks (10220038). Jun2025, Vol. 31 Issue 5, p3533-3553. 21p. |
| Subjects: | Intelligent networks, Telecommunication, Artificial intelligence, Traffic congestion, Energy consumption, Multicasting (Computer networks), Wireless sensor networks, Data transmission systems |
| Abstract: | The transmission of large volumes of sensor node data is the biggest challenge for IoT networks. Communication power overuse threatens nodes' survivability. Thus, network challenges including QoS, security, network heterogeneity, congestion avoidance, reliable routing, and energy savings must be addressed. Data transmission between companies requires routing mechanisms. Data aggregation is critical to reducing traffic congestion, operational costs, energy use, and network lifetime. When IoT data is consolidated, route planning for reliability, energy efficiency, and effectiveness is tough. This work presents Cluster-based energy-aware & nearest adjacent neighbour (CEAAN), a novel routing approach using NS2 simulation. This approach predicts delivery success using decision trees and neural networks. We consider CEAAN routing scheme predictability, node popularity, power consumption, speed, and location during model training. According to simulations, CEAAN outperforms NS2's trustworthy routing scheme in terms of successful delivery, lost messages, overhead, and hop count. However, these changes only slightly enhance buffer length and occupancy. The hybrid routing technique entails cluster construction, as well as intra- and inter-cluster routing. CEAAN outperformed earlier studies in network resilience, packet transmission efficiency, end-to-end latency, and energy utilization. [ABSTRACT FROM AUTHOR] |
| Copyright of Wireless Networks (10220038) is the property of Springer Nature 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 |
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| Header | DbId: egs DbLabel: Engineering Source An: 185649226 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Improving energy efficiency via the use of IoT technologies with intelligent network clustering. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Abujassar%2C+Radwan+S%2E%22">Abujassar, Radwan S.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> r.abujassar@aou.edu.kw</i><br /><searchLink fieldCode="AR" term="%22Al-Jarrah%2C+Omar%22">Al-Jarrah, Omar</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> o.aljarrah@arabou.edu.kw</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Wireless+Networks+%2810220038%29%22">Wireless Networks (10220038)</searchLink>. Jun2025, Vol. 31 Issue 5, p3533-3553. 21p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Intelligent+networks%22">Intelligent networks</searchLink><br /><searchLink fieldCode="DE" term="%22Telecommunication%22">Telecommunication</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+intelligence%22">Artificial intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22Traffic+congestion%22">Traffic congestion</searchLink><br /><searchLink fieldCode="DE" term="%22Energy+consumption%22">Energy consumption</searchLink><br /><searchLink fieldCode="DE" term="%22Multicasting+%28Computer+networks%29%22">Multicasting (Computer networks)</searchLink><br /><searchLink fieldCode="DE" term="%22Wireless+sensor+networks%22">Wireless sensor networks</searchLink><br /><searchLink fieldCode="DE" term="%22Data+transmission+systems%22">Data transmission systems</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The transmission of large volumes of sensor node data is the biggest challenge for IoT networks. Communication power overuse threatens nodes' survivability. Thus, network challenges including QoS, security, network heterogeneity, congestion avoidance, reliable routing, and energy savings must be addressed. Data transmission between companies requires routing mechanisms. Data aggregation is critical to reducing traffic congestion, operational costs, energy use, and network lifetime. When IoT data is consolidated, route planning for reliability, energy efficiency, and effectiveness is tough. This work presents Cluster-based energy-aware & nearest adjacent neighbour (CEAAN), a novel routing approach using NS2 simulation. This approach predicts delivery success using decision trees and neural networks. We consider CEAAN routing scheme predictability, node popularity, power consumption, speed, and location during model training. According to simulations, CEAAN outperforms NS2's trustworthy routing scheme in terms of successful delivery, lost messages, overhead, and hop count. However, these changes only slightly enhance buffer length and occupancy. The hybrid routing technique entails cluster construction, as well as intra- and inter-cluster routing. CEAAN outperformed earlier studies in network resilience, packet transmission efficiency, end-to-end latency, and energy utilization. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Wireless Networks (10220038) is the property of Springer Nature 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.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=185649226 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1007/s11276-025-03948-w Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 21 StartPage: 3533 Subjects: – SubjectFull: Intelligent networks Type: general – SubjectFull: Telecommunication Type: general – SubjectFull: Artificial intelligence Type: general – SubjectFull: Traffic congestion Type: general – SubjectFull: Energy consumption Type: general – SubjectFull: Multicasting (Computer networks) Type: general – SubjectFull: Wireless sensor networks Type: general – SubjectFull: Data transmission systems Type: general Titles: – TitleFull: Improving energy efficiency via the use of IoT technologies with intelligent network clustering. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Abujassar, Radwan S. – PersonEntity: Name: NameFull: Al-Jarrah, Omar IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2025 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 10220038 Numbering: – Type: volume Value: 31 – Type: issue Value: 5 Titles: – TitleFull: Wireless Networks (10220038) Type: main |
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