An adaptive IOTA-based smart-contract framework for secure and scalable information extraction in WSN-based IoT
- Tariq Alsboui(corresponding author),
- Hussain Al-Aqrabi,
- Ahmed Manasrah,
- Mohammad Hijjawi,
- Edge Hill University,
- Higher Colleges of Technology,
- Yarmouk University,
- Applied Science Private University,
- ,
Open access
Abstract
Wireless Sensor Networks (WSNs) are a core component of the Internet of Things (IoT), but they still face challenges in processing heterogeneous data, coordinating distributed nodes, and maintaining timely and verifiable operation. This paper proposes an adaptive IOTA-based smart-contract framework for secure and scalable information extraction in WSN–IoT systems. The framework uses a three-layer architecture with event-driven and time-driven execution modes, a deterministic state-aware controller for mode switching, DAG-based primary and secondary cluster-head selection, and mobile-agent collection from selected cluster heads. The framework is evaluated through WSN-side simulations of the adaptive-control, clustering, and mobile-agent components, while the ledger-facing workflow is demonstrated through an IOTA EVM proof of concept using encrypted local content storage and on-chain content-reference anchoring. At 150 nodes, event-driven execution achieves a 74.11% completion ratio, whereas the time-driven and adaptive modes maintain 100% completion. The adaptive mode completes 4424.70 operations per workload minute, 34.94% more than event-driven execution, and achieves a mean paired per-run latency reduction of 6.73% relative to fixed time-driven execution, with a 95% confidence interval of 2.80–10.65%. The reported performance results exclude cryptographic processing, JSON-RPC communication, EVM execution, transaction inclusion, ledger confirmation, and native IOTA Streams publication.
Publication Information
Output type
Original language
EnglishArticle number
102057Journal (Volume, Issue Number)
Internet of Things (The Netherlands) (Volume 39)Publication milestones
- E-pub ahead of print - 07/08/2026
- Published - 07/08/2026
Publication status
Publication IDs
- Scopus: 105046908717
