Real-Time Containers: A Survey

Container-based virtualization has gained a significant importance in a deployment of software applications in cloud-based environments. The technology fully relies on operating system features and does not require a virtualization layer (hypervisor) that introduces a performance degradation. Container-based virtualization allows to co-locate multiple isolated containers on a single computation node as well as to decompose an application into multiple containers distributed among several hosts (e.g., in fog computing layer). Such a technology seems very promising in other domains as well, e.g., in industrial automation, automotive, and aviation industry where mixed criticality containerized applications from various vendors can be co-located on shared resources. However, such industrial domains often require real-time behavior (i.e, a capability to meet predefined deadlines). These capabilities are not fully supported by the container-based virtualization yet. In this work, we provide a systematic literature survey study that summarizes the effort of the research community on bringing real-time properties in container-based virtualization. We categorize existing work into main research areas and identify possible immature points of the technology

Constant bandwidth servers with constrained deadlines

The Hard Constant Bandwidth Server (H-CBS) is a reservation-based scheduling algorithm often used to mix hard and soft real-time tasks on the same system. A number of variants of the H-CBS algorithm have been proposed in the last years, but all of them have been conceived for implicit server deadlines (i.e., equal to the server period). However, recent promising results on semi-partitioned scheduling together with the demand for new functionality claimed by the Linux community, urge the need for a reservation algorithm that is able to work with constrained deadlines. This paper presents three novel H-CBS algorithms that support constrained deadlines. The three algorithms are formally analyzed, and their performance are compared through an extensive set of simulations

Scheduling for Mixed-criticality Hypervisor Systems in the Automotive Domain

This thesis focuses on scheduling for hypervisor systems in the automotive domain. Current practices are primarily implementation-agnostic or are limited by lack of visibility during the execution of partitions. The tasks executed within the partitions are classified as event-triggered or time-triggered. A scheduling model is developed using a pair of a deferrable server and a periodic server per partition to provide low latency for event-triggered tasks and maximising utilisation. The developed approach enforces temporal isolation between partitions and ensures that time-triggered tasks do not suffer from starvation. The scheduling model was extended to support three criticality levels with two degraded modes. The first degraded mode provides the partitions with additional capacity by trading-off low latency of event-driven tasks with lower overheads and utilisation. Both models were evaluated by forming a case study using real ECU application code. A second case study was formed inspired from the Olympus Attitude and Orbital Control System (AOCS) to further evaluate the proposed mixed-criticality model. To conclude, the contributions of this thesis are addressed with respect to the research hypothesis and possible avenues for future work are identified