Academic Journal

A fuzzy logic-based extremal optimization approach for enhancing energy efficiency in wireless sensor networks.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: A fuzzy logic-based extremal optimization approach for enhancing energy efficiency in wireless sensor networks.
Συγγραφείς: Tabatabaei, S.
Πηγή: Iranian Journal of Fuzzy Systems; Mar/Apr2026, Vol. 23 Issue 2, p37-52, 16p
Θεματικοί όροι: Wireless sensor networks, Energy consumption, Data transmission systems, End-to-end delay, Mathematical optimization, Network routing protocols, Fuzzy logic
Περίληψη: A wireless sensor network (WSN) consists of a collection of sensor nodes that collaboratively perform monitoring and data acquisition tasks. Considering the strict resource limitations of sensor nodes, achieving high energy efficiency is a critical requirement. In WSNs, it is essential to minimize data collection delay to ensure that sensed information remains current, while simultaneously maximizing the number of collected data samples to enhance accuracy and reliability. To address these conflicting objectives, this paper proposes a clustering-based routing protocol that simultaneously maximizes packet delivery, minimizes energy consumption, and reduces end-to-end delay. The proposed protocol integrates extremal optimization with fuzzy logic to dynamically form clusters, selecting cluster heads based on two primary criteria: residual energy and distance to the sink. The elected cluster heads then construct a minimum spanning tree (MST) to serve as an efficient multi-hop communication backbone toward the sink. The proposed method, termed the Extremal Optimization Fuzzy-Based Clustering Algorithm (EOFBCA), was implemented and evaluated using the OPNET 11.5 simulation platform. Performance is compared against three state-of-the-art protocols: AFSRP, BFOABMS, and NODIC. Simulation results demonstrate that EOFBCA achieves superior performance across multiple metrics, including energy consumption, end-to-end delay, throughput, packet delivery ratio, and signal-to-noise ratio. [ABSTRACT FROM AUTHOR]
Copyright of Iranian Journal of Fuzzy Systems is the property of University of Sistan & Baluchestan 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.)
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  Data: A fuzzy logic-based extremal optimization approach for enhancing energy efficiency in wireless sensor networks.
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  Data: Iranian Journal of Fuzzy Systems; Mar/Apr2026, Vol. 23 Issue 2, p37-52, 16p
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  Data: <searchLink fieldCode="DE" term="%22Wireless+sensor+networks%22">Wireless sensor networks</searchLink><br /><searchLink fieldCode="DE" term="%22Energy+consumption%22">Energy consumption</searchLink><br /><searchLink fieldCode="DE" term="%22Data+transmission+systems%22">Data transmission systems</searchLink><br /><searchLink fieldCode="DE" term="%22End-to-end+delay%22">End-to-end delay</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Network+routing+protocols%22">Network routing protocols</searchLink><br /><searchLink fieldCode="DE" term="%22Fuzzy+logic%22">Fuzzy logic</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: A wireless sensor network (WSN) consists of a collection of sensor nodes that collaboratively perform monitoring and data acquisition tasks. Considering the strict resource limitations of sensor nodes, achieving high energy efficiency is a critical requirement. In WSNs, it is essential to minimize data collection delay to ensure that sensed information remains current, while simultaneously maximizing the number of collected data samples to enhance accuracy and reliability. To address these conflicting objectives, this paper proposes a clustering-based routing protocol that simultaneously maximizes packet delivery, minimizes energy consumption, and reduces end-to-end delay. The proposed protocol integrates extremal optimization with fuzzy logic to dynamically form clusters, selecting cluster heads based on two primary criteria: residual energy and distance to the sink. The elected cluster heads then construct a minimum spanning tree (MST) to serve as an efficient multi-hop communication backbone toward the sink. The proposed method, termed the Extremal Optimization Fuzzy-Based Clustering Algorithm (EOFBCA), was implemented and evaluated using the OPNET 11.5 simulation platform. Performance is compared against three state-of-the-art protocols: AFSRP, BFOABMS, and NODIC. Simulation results demonstrate that EOFBCA achieves superior performance across multiple metrics, including energy consumption, end-to-end delay, throughput, packet delivery ratio, and signal-to-noise ratio. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of Iranian Journal of Fuzzy Systems is the property of University of Sistan & Baluchestan 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.)
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RecordInfo BibRecord:
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      – Type: doi
        Value: 10.22111/ijfs.2026.52619.9292
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      – Code: eng
        Text: English
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        PageCount: 16
        StartPage: 37
    Subjects:
      – SubjectFull: Wireless sensor networks
        Type: general
      – SubjectFull: Energy consumption
        Type: general
      – SubjectFull: Data transmission systems
        Type: general
      – SubjectFull: End-to-end delay
        Type: general
      – SubjectFull: Mathematical optimization
        Type: general
      – SubjectFull: Network routing protocols
        Type: general
      – SubjectFull: Fuzzy logic
        Type: general
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              M: 03
              Text: Mar/Apr2026
              Type: published
              Y: 2026
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