Deadline-aware workload scheduling for edge-enhanced iot devices: A blockchain-enabled approach to incentive-based computing

This paper explore Blockchain-enabled incentive-driven workload scheduling for deadline-sensitive computational tasks over edge devices in mission critical applications such as healthcare, autonomous vehicles, and smart cities. Leveraging the power of volunteer edge devices, our study addresses the critical challenge of meeting job deadlines to optimize revenue and minimize penalties. We introduce a novel deadline-aware scheduling approach, augmented by classical algorithms like First Come First Serve (FCFS), First Fit, and Best Fit, as well as state-of-the-art counterparts, for robust comparative analysis. By integrating bin packing techniques and computational resource boosting on volunteer edge devices, the proposed method ensures effective deadline adherence. Additionally, we propose innovative mechanisms for volunteer edge device ranking and penalty-reward calculations to further enhance system efficiency. To ensure transparency and trust, the proposed system utilizes blockchain to securely log work activities and facilitate incentive payments. The proposed framework is comprehensively evaluated across ten key metrics such as completion time, deadline violations, penalties, device income, and device rankings using the Bitbrains workload traces. The results underscore the significant advantages of our deadline-aware algorithm, showcasing improvements ranging from 4% to 44% across all metrics, including enhanced income for volunteer devices, improved time efficiency, balanced workload distribution, and reduced deadline violations.