A trust-based fuzzy neural network for smart data fusion in internet of things
•Towards improvement of the smart data fusion using fuzzy neural network for IoT.•Proposed a trust-based neural network model for solving the IoT data storage problems.•It enhances the and storage efficiency with minimum energy consumption.•By distributing data to nodes without the defuzzification p...
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Published in | Computers & electrical engineering Vol. 89; p. 106901 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Elsevier Ltd
01.01.2021
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Subjects | |
Online Access | Get full text |
ISSN | 0045-7906 |
DOI | 10.1016/j.compeleceng.2020.106901 |
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Abstract | •Towards improvement of the smart data fusion using fuzzy neural network for IoT.•Proposed a trust-based neural network model for solving the IoT data storage problems.•It enhances the and storage efficiency with minimum energy consumption.•By distributing data to nodes without the defuzzification process.•Performed an adequate data storage via Trust Mechanism.
Internet of Things (IoT) devices generates a vast amount of data from extensive applications. Maintaining the sensed data with low energy consumption, delay time, and adaptive coverage fraction rate proportionally influences the storage capacity. To maintain a trade-off between above-listed factors, we proposed an Elfes Sugeno Fuzzy and Trust-based Neural Networks (ESF-TNN) approach enables 3-algorithms. First, Elfes Probability Sensing (EPS) Model addresses the coverage fraction of each IoT sensor. Second, Sugeno Fuzzy Processing model regulates the energy consumption by proportionately distributing data to nodes without the defuzzification process. Third, Trust-based Neural Data Storage algorithm enriches an adequate data storage capacity by considering the average classification ratio while processing regenerated data packets to pertain each interaction information via Trust Mechanism. Simulation results show that our proposed method effectively covers the monitored area with 15 Joules of energy consumption and 1-ms delay time along with sufficient storage capacity.
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AbstractList | •Towards improvement of the smart data fusion using fuzzy neural network for IoT.•Proposed a trust-based neural network model for solving the IoT data storage problems.•It enhances the and storage efficiency with minimum energy consumption.•By distributing data to nodes without the defuzzification process.•Performed an adequate data storage via Trust Mechanism.
Internet of Things (IoT) devices generates a vast amount of data from extensive applications. Maintaining the sensed data with low energy consumption, delay time, and adaptive coverage fraction rate proportionally influences the storage capacity. To maintain a trade-off between above-listed factors, we proposed an Elfes Sugeno Fuzzy and Trust-based Neural Networks (ESF-TNN) approach enables 3-algorithms. First, Elfes Probability Sensing (EPS) Model addresses the coverage fraction of each IoT sensor. Second, Sugeno Fuzzy Processing model regulates the energy consumption by proportionately distributing data to nodes without the defuzzification process. Third, Trust-based Neural Data Storage algorithm enriches an adequate data storage capacity by considering the average classification ratio while processing regenerated data packets to pertain each interaction information via Trust Mechanism. Simulation results show that our proposed method effectively covers the monitored area with 15 Joules of energy consumption and 1-ms delay time along with sufficient storage capacity.
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ArticleNumber | 106901 |
Author | Malchi, Sunil Kumar Al-Turjman, Fadi Patan, Rizwan Kallam, Suresh |
Author_xml | – sequence: 1 givenname: Sunil Kumar surname: Malchi fullname: Malchi, Sunil Kumar organization: Department of Computer Science and Engineering, Sree Vidyanikethan Engineering College, Tirupati, Andhra Pradesh, 517102, India – sequence: 2 givenname: Suresh surname: Kallam fullname: Kallam, Suresh organization: Department of Computer Science and Engineering, Sree Vidyanikethan Engineering College, Tirupati, Andhra Pradesh, 517102, India – sequence: 3 givenname: Fadi surname: Al-Turjman fullname: Al-Turjman, Fadi organization: Research Centre for AI and IoT, Artificial Intelligence Engineering Dept., Near East University, Nicosia, Mersin 10, Turkey – sequence: 4 givenname: Rizwan surname: Patan fullname: Patan, Rizwan email: rizwan@vrsiddhartha.ac.in organization: Department of Computer Science and Engineering, Velagapudi Ramakrishna Siddhartha Engineering College, Vijayawada, Andhra Pradesh, 520007, India |
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Title | A trust-based fuzzy neural network for smart data fusion in internet of things |
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