Academic Journal

Integrating digital twins for optimized off-chain processing in decentralized systems.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Integrating digital twins for optimized off-chain processing in decentralized systems.
Συγγραφείς: El-Hajj, Mohammed
Πηγή: Frontiers in Blockchain; 2026, p1-22, 22p
Θεματικοί όροι: Digital twin, Blockchains, Internet of things, Energy consumption, Security management, Electronic data processing, Mathematical optimization
Περίληψη: Digital Twins are becoming essential for optimizing decentralized systems through real-time data processing and off-chain analytics. However, existing solutions often face challenges such as high latency, limited scalability, and weak synchronization between physical and virtual entities. This study introduces a novel framework that integrates DTs with blockchain to enhance off-chain processing efficiency while preserving security and data integrity. Using IoT sensor data and a test environment built with Ganache, Flask, and Python-based optimization models, the proposed system achieved throughput levels of up to 500 transactions per second and reduced latency by 50% compared to a traditional baseline, with processing times consistently under 150 m. It maintained a transaction success rate above 90% under moderate load (30–40 concurrent Digital Twins) and approximately 70% with 100 concurrent Digital Twins under high-stress conditions. The framework also demonstrated strong resource efficiency, averaging 50% CPU and 40% memory usage, while reducing energy consumption by 33%–41% across low, moderate, and high load scenarios. A comprehensive cost-effectiveness analysis revealed a 35.2% reduction in total cost of ownership (TCO) over a 3-year period, with a return on investment (ROI) of 140%. Security assessments confirmed resilience against common attack vectors. These results highlight the system's potential as a scalable, secure, energy-efficient, and economically viable solution for decentralized applications in smart cities and industrial IoT environments. [ABSTRACT FROM AUTHOR]
Copyright of Frontiers in Blockchain is the property of Frontiers Media S.A. 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.)
Βάση Δεδομένων: Complementary Index
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  Data: Integrating digital twins for optimized off-chain processing in decentralized systems.
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  Data: <searchLink fieldCode="AR" term="%22El-Hajj%2C+Mohammed%22">El-Hajj, Mohammed</searchLink>
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  Data: Frontiers in Blockchain; 2026, p1-22, 22p
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  Data: <searchLink fieldCode="DE" term="%22Digital+twin%22">Digital twin</searchLink><br /><searchLink fieldCode="DE" term="%22Blockchains%22">Blockchains</searchLink><br /><searchLink fieldCode="DE" term="%22Internet+of+things%22">Internet of things</searchLink><br /><searchLink fieldCode="DE" term="%22Energy+consumption%22">Energy consumption</searchLink><br /><searchLink fieldCode="DE" term="%22Security+management%22">Security management</searchLink><br /><searchLink fieldCode="DE" term="%22Electronic+data+processing%22">Electronic data processing</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink>
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  Data: Digital Twins are becoming essential for optimizing decentralized systems through real-time data processing and off-chain analytics. However, existing solutions often face challenges such as high latency, limited scalability, and weak synchronization between physical and virtual entities. This study introduces a novel framework that integrates DTs with blockchain to enhance off-chain processing efficiency while preserving security and data integrity. Using IoT sensor data and a test environment built with Ganache, Flask, and Python-based optimization models, the proposed system achieved throughput levels of up to 500 transactions per second and reduced latency by 50% compared to a traditional baseline, with processing times consistently under 150 m. It maintained a transaction success rate above 90% under moderate load (30–40 concurrent Digital Twins) and approximately 70% with 100 concurrent Digital Twins under high-stress conditions. The framework also demonstrated strong resource efficiency, averaging 50% CPU and 40% memory usage, while reducing energy consumption by 33%–41% across low, moderate, and high load scenarios. A comprehensive cost-effectiveness analysis revealed a 35.2% reduction in total cost of ownership (TCO) over a 3-year period, with a return on investment (ROI) of 140%. Security assessments confirmed resilience against common attack vectors. These results highlight the system's potential as a scalable, secure, energy-efficient, and economically viable solution for decentralized applications in smart cities and industrial IoT environments. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of Frontiers in Blockchain is the property of Frontiers Media S.A. 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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        Value: 10.3389/fbloc.2026.1719622
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      – Code: eng
        Text: English
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        PageCount: 22
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      – SubjectFull: Digital twin
        Type: general
      – SubjectFull: Blockchains
        Type: general
      – SubjectFull: Internet of things
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      – SubjectFull: Energy consumption
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      – SubjectFull: Security management
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      – SubjectFull: Electronic data processing
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      – SubjectFull: Mathematical optimization
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              Text: 2026
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