Container scheduling techniques: A Survey and assessment

Containers have emerged as the most promising lightweight virtualization technology in providing cloud services due to its flexible deployment, portability, and scalability especially in micro-services, smart vehicles, IoTs, and fog/edge computing. An important and vital role in cloud container services is played by the scheduler's component to optimize performance and reduce cost due to the diverse nature of the workload and cloud resources. Despite the immense traction of containers in cloud computing, there is no comprehensive survey that covers container scheduling techniques. In this timely survey, we investigate the landscape of the state-of-the-art container scheduling techniques aiming to inspire more research work in this active area of research. The survey is structured around classifying the scheduling techniques into four categories based on the type of optimization algorithm employed to generate the schedule namely mathematical modeling, heuristics, meta-heuristics and machine learning. Then for each class of scheduling algorithms, we analyze and identify key benefits and pitfalls, together with key challenges of the available techniques based on the performance metrics. Finally, this paper highlights fertile future research opportunities to realize the full potential of the emergent container technology.