Exploring microservices for enhancing internet QoS

With the enhancements in the field of software-defined networking and virtualization technologies, novel networking paradigms such as network function virtualization and the Internet of Things are rapidly gaining ground. The development of Internet of Things and 5G networks and explosion in online services has resulted in an exponential growth of devices connected to the network. As a result, application service providers and Internet service providers are being confronted with the unprecedented challenge of accommodating increasing service and traffic demands from the geographically distributed users. To tackle this problem, many and ISPs, such as Netflix, Facebook, and AT&T, are increasingly adopting microservices application architecture. Despite the success of microservices in the industry, there is no specific standard or research work for service providers as guidelines, especially from the perspective of basic microservice operations. In this work, we aim to bridge this gap between the industry and the academia and discuss different microservice deployment, discovery, and communication options for service providers as a means to forming complete service chains. In addition, we address the problem of scheduling microservices across multiple clouds, including microclouds. We consider different user-level service level agreements, such as latency and cost, while scheduling such services. We aim to reduce the overall turnaround time and costs for the deployment of complete end-to-end service. In this work, we present a novel affinity-based fair weighted scheduling heuristic to solve this problem. We also compare the results of the proposed solution with standard greedy scheduling algorithms presented in the literature and observe significant improvements.