工业物联网中基于边缘计算的跨域计算资源分配与任务卸载

Cross-domain task offloading and computing resource allocation for edge computation in industrial Internet of things

在工业物联网中,现场设备的计算能力有限,基于边缘计算的任务卸载可以有效缓解现场设备的计算压力,提供低时延计算服务。此外,由于网络中不同区域的边缘服务器负载不同,需要合理安排任务卸载以及分配边缘服务器计算资源,从而降低任务完成时延,实现负载均衡。因此,研究了工业物联网中基于边缘计算的任务卸载和资源分配,提出了一种工业物联网中计算任务跨域卸载模型,并构建了一个最小化任务完成时间的混合整数非线性优化问题。将该问题分解为资源分配与任务卸载两个子问题,基于两个子问题特征,通过迭代交替求解,得到资源分配最优解与任务卸载策略。实验结果表明,与不跨域方法相比,所提方法有效地减轻了边缘服务器的负载不均衡,减少了任务完成时延。

In the industrial Internet of things,limited by the computing capacity of field devices,the task offloading based on edge computing can effectively alleviate the computing burden of field devices and provide low-latency computing services.Moreover,because the load of edge servers are different in different areas of the network,it is necessary to reasonably arrange task offloading and allocate computing resources of edge servers,thereby reducing task completion delay and achieving load balance.Thus,the task offloading and resource allocation for edge computing in the industrial Internet of things was studied,a cross-domain offloading model for computing tasks in the industrial Internet of things was proposed,and a mixed integer nonlinear optimization problem that minimizes task completion time was formulated.The problem was decomposed it into two sub-problems of resource allocation and task offloading,based on the characteristics of the two sub-problems,the optimal solution of resource allocation and task offloading strategy were obtained through iterative and alternating solution.The experimental results show that compared with the non-cross-domain strategy,the load imbalance of the edge server and the task completion delay are reduced effectively by the proposed strategy.