In recent years, there has been a growing interest in supporting component-based software development of complex real-time embedded systems. Techniques such as machine virtualisation have emerged as interesting mechanisms to enhance the security of these platforms, while real-time scheduling techniques have been proposed to guarantee temporal isolation of different virtualised components sharing the same physical resources. This combination also highlighted criticalities due to overheads introduced by hypervisors, particularly for low-end embedded devices. This led to the need of investigating deeper into solutions based on lightweight virtualisation alternatives, such as containers. In this context, this paper proposes to use a real-time deadline-based scheduling policy built into the Linux kernel to provide temporal scheduling guarantees to different co-located containers. The proposed solution extends the SCHED_DEADLINE scheduling policy to schedule Linux control groups, allowing user threads to be scheduled with fixed priorities inside the control group scheduled by SCHED_DEADLINE. The proposed mechanism can be configured via control groups, and it is compatible with commonly used tools such as LXC, Docker and similar. This solution is compatible with existing hierarchical real-time scheduling analysis, and some experiments demonstrate consistency between theory and practice. CCS CONCEPTS • Computer systems organization → Embedded software; Realtime operating systems; • Software and its engineering → Virtual machines;
Computing platforms are evolving towards heterogeneous architectures including processors of different types and field programmable gate arrays (FPGAs), used as hardware accelerators for speeding up specific functions. The increasing capacity and performance of modern FPGAs, with their partial reconfiguration capabilities, have made them attractive in several application domains, including space applications.This paper proposes a framework for supporting the development of safety-critical real-time systems that exploit hardware accelerators developed through FPGAs with dynamic partial reconfiguration capabilities.A model is first presented and then used to derive a response-time analysis to verify the schedulability of a real-time task set under given constraints and assumptions. Although the analysis is based on a generic model, the proposed framework has been conceived to account for several real-world constraints present on today's platforms and has been practically validated on the Zynq platform, showing that it can actually be supported by state-of-the-art technologies. Finally, a number of experiments are reported to evaluate the worst-case performance of the proposed approach on synthetic workload
Providing innovative resource-efficient solutions able to mitigate temporal interference among cloud services, concurrently sharing the same underlying platform, is crucial to deploy highly time-sensitive applications at the edge of the network where resources are strongly restrained, and timing constraints are stringent. A notable example is provided by the allocation of virtualized network functions in the radio access network of modern mobile networks, such as 5G. This paper describes a kernel mechanism that can be applied to the design of an architecture providing fine-grain control of the temporal interferences among concurrent real-time services while avoiding overheads related to machine virtualization. On top of them, a model is proposed to meet the required endto-end application performance through tuning of parameters in the underlying novel architecture. We show that theoretical latency/load curves match closely with experimental data gathered from a real implementation carried out using both a networking microbenchmark and a real IMS application.
In this work, we introduce a power-consumption model for heterogeneous multicore architectures that captures the variability of energy consumption based on processing workload type, in addition to the classical variables considered in the literature, like type and frequency of the CPU. We motivate the approach presenting experimental results gathered on a Odroid-XU3 board equipped with an Arm big.LITTLE CPU, showing that power consumption has a non-negligible dependency on the workload type. We also present a model to define the execution time of the tasks, which depends on both the workload, and the CPU frequency and architecture. We present our modifications to the open-source RTSIM real-time scheduling simulator to extend its CPU power consumption and execution time duration models, integrating results taken from the real platform. The presented work constitutes a useful base for future research in power-aware real-time scheduling on heterogeneous platforms. CCS CONCEPTS • Computer systems organization → Real-time operating systems; Embedded systems;
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