一种面向边缘环境的多实例服务链在线部署算法

边缘设备的资源有限性促使部署边缘服务需要深入理解网络功能的资源消耗情况.通过无线路由器上容器化网络功能部署实验得出,除了处理业务流的计算开销外,网络功能实例间的通信也会消耗大量CPU资源.基于该发现,考虑在近距离和相对低负载的对等边缘设备上分布式地部署网络功能实例,在满足时延约束的条件下均衡流量,从而最小化边缘设备负载...

A multi-instance service chain online deployment algorithm for edge environments

The limited resources of edge devices make it necessary to deeply understand the resource consumption of network functions to deploy edge services. Through the deployment experiment of containerized network functions on wireless routers, it is concluded that in addition to the computational overhead of processing business flows, communication between network function instances will also consume a lot of CPU resources. Based on this observation, the distributed deployment of network function instances on peer-to-peer edge devices at close range and relatively low load is considered, and the traffic under the condition of satisfying delay constraints are balanced, thereby minimizing the edge device load. Therefore, a fine-grained service chain load model is proposed, and on this basis, a multi-instance service chain online deployment algorithm for edge environments is designed and implemented. The algorithm includes three components: the delay satisfaction path search based on the pruning search strategy, the deployment path selection based on the nested Top K strategy, and the network function deployment based on the greedy strategy. Simulation experiments verify the effectiveness of the algorithm. The experimental results show that compared to the deployment of network function chains without considering communication overhead, the algorithm proposed in this paper can reduce the CPU load of edge devices by 10%, which is close to the theoretical optimal deployment result.