面向多工作流的基于容器的边缘微服务选择机制

边缘计算已经成为物联网(IOT)的有效解决方案，微服务模型将物联网应用程序划分为一组松散耦合、相互依赖的细粒度微服务。由于边缘节点资源有限，并发请求争夺容器实例，如何在移动边缘计算环境下为复杂工作流应用的并发请求生成合适的微服务执行方案是一个需要解决的重要问题。为此，该文首先建立了基于容器的微服务选择架构，并构建了服务时延模型和网络资源消耗模型，以减少平均延迟和网络消耗。其次，提出一种基于优先级机制和改进蚁群的微服务选择算法(MS-PAC)，利用任务截止时间优先分配紧急任务以保证延迟，并利用蚁群算法的信息素机制寻找全局最优解。实验表明，该算法能有效地降低平均时延和网络消耗。

Container Based Microservice Selection for Multi-workflow in Edge Computing Paradigm

Edge computing has become an effective solution for the Internet Of Things (IOT) and the microservice model divides the IOT application into a group of loosely coupled and interdependent fine-grained microservices. Due to the limit resource of edge nodes and concurrent requests compete for container instances, how to generate an appropriate microservice selection scheme for concurrent requests of complex workflow application in mobile edge computing environment is an important problem to be solved. Therefore, a container based microservice selection architecture is established in this paper firstly, and the service delay model and network resource consumption model are constructed to reduce the average delay and network consumption. Secondly, Microservice Selection algorithm based on Priority mechanism and improved Ant Colony (MS-PAC) based on priority mechanism and improved ant colony algorithm is proposed, which uses the task deadline to assign urgent tasks first to ensure the delay, and uses the pheromone mechanism of ant colony algorithm to find the global optimal solution. Experimentation demonstrates that the proposed algorithm can reduce the average delay and network consumption effectively.