Abstract:

Limited by the long distance communication between the cloud and the end device,processing data only on the cloud can no longer meet the needs of time-sensitive applications,which prompts some applications to expand to the lower edge devices.With the rapid development of embedded systems,fog computing has become a new computing paradigm that connects cloud and end devices to execute applications closer to data sources.The computing capability of the fog layer is usually derived from high-performance heterogeneous embedded board.Different mapping and placement strategies of services in the fog layer have a great impact on resource utilization of devices in the fog layer.Most of the existing service placement strategies aim at improving the system Quality of Service (QoS),but ignore the heterogeneity of embedded devices and the limitation of computing resources,which leads to the decrease in resource utilization.To solve the above problems,this paper proposes a service placement strategy for fog computing applications.Based on the micro-service architecture,the heterogeneous resources in the fog computing layer are optimized and modeled,and the heterogeneous resource attribute characterization is refined.On the basis of ensuring the system,the system resource utilization rate is improved through dynamic comparison of service placement consumption.Comparing the proposed strategy with both the request rate-based placement strategy and the iFogSim default placement strategy,the system resource utilization of the proposed strategy increases by 10.7% and 28.7%,respectively.

Key words: embedded architecture, heterogeneous resources, containers, fog computing, microservice placement