Computational task offloading based on edge computing can deal with the performance bottleneck faced by traditional cloud-based systems for industrial Internet of things (IIoT). To further optimize computing efficiency and resource allocation, collaborative offloading has been put forward to enable the offloading from edge devices to IIoT terminal devices. However, there still lack incentive mechanisms to encourage participants to take over the tasks from others. To counter this situation, this paper proposes a distributed computational resource trading strategy addressing multiple preferences of IIoT users. Unlike most existing works, the objective of our trading strategy comprehensively considers different satisfaction degrees with task delay, energy consumption, price, and user reputation of both requesters and collaborators. The system design uses blockchain to enhance the decentralization, security, and automation. Compared with the trading method based on classical double auction matching mechanism, our trading strategy has more tasks offloaded and executed, and the trading results are friendlier to collaborators with good reputation.
翻译:以边缘计算为基础的卸载计算任务可以解决传统基于云的工业物互联网系统所面临的工作瓶颈问题。为了进一步优化计算效率和资源分配,已经开展了协作卸载工作,以便能够从边缘设备卸载到二手终端设备。然而,仍然缺乏激励机制鼓励参与者接管他人的任务。为了应对这种情况,本文件建议了一种分布式计算资源交易战略,解决二手用户的多重偏好。与大多数现有工程不同,我们贸易战略的目标全面考虑了任务延迟、能源消耗、价格和用户声誉等不同程度的满意度。系统设计使用了块链以加强分散、安全和自动化。与基于传统的双拍卖匹配机制的贸易方法相比,我们的贸易战略有较多的任务卸载和执行,而交易结果与良好声誉的合作者相比更为友好。