Optimal edge-cloud collaboration based strategies for minimizing valid latency of railway environment monitoring system

Abstract

Response speed is vital for the railway environment monitoring system, especially for the sudden-onset disasters. The edge-cloud collaboration scheme is proved efficient to reduce the latency. However, the data characteristics and communication demand of the tasks in the railway environment monitoring system are all different and changeable, and the latency contribution of each task to the system is discrepant. Hence, two valid latency minimization strategies based on the edge-cloud collaboration scheme is developed in this paper. First, the processing resources are allocated to the tasks based on the priorities, and the tasks are processed parallelly with the allocated resources to minimize the system valid latency. Furthermore, considering the differences in the data volume of the tasks, which will induce the waste of the resources for the tasks finished in advance. Thus, the tasks with similar priorities are graded into the same group, and the serial and parallel processing strategies are performed intra-group and inter-group simultaneously. Compared with the other four strategies in four railway monitoring scenarios, the proposed strategies proved latency efficiency to the high-priority tasks, and the system valid latency is reduced synchronously. The performance of the railway environment monitoring system in security and efficiency will be promoted greatly with the proposed scheme and strategies.