Design and Evaluation of a Microservice Testing Tool for Edge Computing Environments

Abstract: Edge computing can provide decentralized computation and storage resources with low latency and high bandwidth. It is a promising infrastructure to host services with stringent latency requirements, for example autonomous driving, cloud gaming, and telesurgery to the customers. Because of the structural complexity associated with the edge computing applications, research topics like service placement gain great importance. To provide a realistic and efficient general environment for evaluating service placement solutions that can be used to analyze latency requirements of services at scale, a new testing tool for mobile edge cloud is designed and implemented in this thesis. The proposed tool is implemented as a cloud native application, and allows deploying applications in an edge computing infrastructure that consists of Kubernetes and Istio, it can be easily scaled up to several hundreds of microservices, and deployment into the edge clusters is automated. With the help of the designed tool, two different microservice placement algorithms are evaluated in an emulated edge computing environment based on Federated Kubernetes. The results have shown how the performance of algorithms varies when the parameters of the environment, and the applications instantiated and deployed by the tool are changed. For example, increasing the request rate 200% can increase the delay by 100% for different algorithms. Moreover, complicating the mobile network can improve the latency performance up to 20% depending on the microservice placement algorithm.