Proteus, a Hybrid Virtualization Platform for Embedded Systems

Baldin, Daniel; Kerstan, Timo

doi:10.1007/978-3-642-04284-3_17

Cited by 14 publications

(8 citation statements)

References 5 publications

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“…Along the Pareto front, the area of reached final points contracts and thus system performance increases as desired. 12 A similar behavior can be observed for the final velocities.…”

Section: Application Examplesupporting

confidence: 76%

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Methods of Improving the Dependability of Self-optimizing Systems

Dorociak

Gausemeier

2014

Lecture Notes in Mechanical Engineering

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Abstract. Various methods have been developed in the Collaborative ResearchCenter 614 which can be used to improve the dependability of self-optimizing systems. These methods are presented in this chapter. They are sorted into two categories with regard to the development process of self-optimizing systems. On one hand, there are methods which can be applied during the Conceptual Design Phase. On the other hand, there are methods that are applicable during Design and Development.There are domain-spanning methods as well as methods that have been specifically developed for particular domains, e.g., software engineering or control engineering. The methods address different attributes of dependability, such as reliability, availability or safety.Each section is prefaced with a short overview of the classification of the described method regarding the corresponding domain(s), as well as its dependability attributes, to provide the reader with a brief outline of the methods' areas of application. Information about independently applicable methods or existing relationships and interactions with other methods or third-party literature is also provided.The development process for self-optimizing mechatronic systems which was introduced in Chap. 2 consists of two main phases: Conceptual Design and Design and Development. The main result of the Conceptual Design is the Principle Solution, which includes all information required for the concrete development during the second phase. Conceptual Design PhaseEven as early as during the specification of the Principle Solution, the dependability of self-optimizing mechatronic systems can be evaluated and improved by employing appropriate methods. The result is an improved Principle Solution, as such methods take the whole system into account before splitting it up into domain-specific tasks for the following development phase.

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“…Along the Pareto front, the area of reached final points contracts and thus system performance increases as desired. 12 A similar behavior can be observed for the final velocities.…”

Section: Application Examplesupporting

confidence: 76%

“…Proteus [12,61] is a real-time hypervisor for multi-core PowerPC platforms. The software design (depicted in Fig.…”

Section: Resultsmentioning

confidence: 99%

Methods of Improving the Dependability of Self-optimizing Systems

Dorociak

Gausemeier

2014

Lecture Notes in Mechanical Engineering

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“…We integrate it into our real-time hypervisor Proteus [1]. The implementation of our approach requires paravirtualization, since the guest-level FRMs have to pass information to the hypervisor.…”

Section: Resultsmentioning

confidence: 99%

Architecture for adaptive resource assignment to virtualized mixed-criticality real-time systems

2013

Self Cite

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System virtualization is a powerful approach for the creation of integrated systems, which meet the high functionality and reliability requirements of complex embedded applications. It is in particular well-suited for mixed-criticality systems, since the often applied pessimistic manner of critical system engineering leads to heavily under-utilized resources. Existing static resource management approaches for virtualized systems are inappropriate for the dynamically varying resource requirements of upcoming adaptive systems. In this paper, we propose a dynamic resource management protocol for system virtualization that factors criticality levels in and allows the addition of subsystems at runtime. The two-level architecture offers flexibility across virtual machine borders and has the potential to improve the resource utilization. In addition, it provides the capability to adapt at runtime according to defects or changes of the environment.

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“…Embedded virtualization (Baldin and Kerstan, 2009;Wind River, 2010) is an emerging concept of the industry, inspired by the success of server and desktop virtualization solutions. Its key goals are similar to that of the partitioning, namely the spatial and temporal separation of software components sharing the same hardware resources, moreover, it enables the utilization of different operating systems in the virtual machines allowing the integration of subsystems of mixed criticality while maintaining the error containment regions.…”

Section: Related Work In Software Integrationmentioning

confidence: 99%

A software integration approach for designing and assessing dependable embedded systems

Suri

Jhumka

Hiller

et al. 2010

Journal of Systems and Software

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a b s t r a c tEmbedded systems increasingly entail complex issues of hardware-software (HW-SW) co-design. As the number and range of SW functional components typically exceed the finite HW resources, a common approach is that of resource sharing (i.e., the deployment of diverse SW functionalities onto the same HW resources). Consequently, to result in a meaningful co-design solution, one needs to factor the issues of processing capability, power, communication bandwidth, precedence relations, real-time deadlines, space, and cost. As SW functions of diverse criticality (e.g. brake control and infotainment functions) get integrated, an explicit integration requirement need is to carefully plan resource sharing such that faults in low-criticality functions do not affect higher-criticality functions.On this background, the main contribution of this paper is a dependability-driven framework that helps to conduct the integration of SW components onto HW resources such that the maintenance of system dependability over integration of diverse criticality components is assured by design.We first develop a clustering strategy for SW components into Fault Containment Modules (FCMs) such that error propagation via interaction is minimized. Subsequently, the rules of composition for FCMs with respect to error propagation are developed. To allocate the resulting FCMs to the existing HW resources we provide several heuristics, each optimizing particular attributes thereof. Further, a framework for assessing the goodness of the achieved HW-SW composition as a dependable embedded system is presented. Two new techniques for quantifying the goodness of the proposed mappings are introduced by examples, both based on a multi-criteria decision theoretic approach.

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Proteus, a Hybrid Virtualization Platform for Embedded Systems

Cited by 14 publications

References 5 publications

Methods of Improving the Dependability of Self-optimizing Systems

Methods of Improving the Dependability of Self-optimizing Systems

Architecture for adaptive resource assignment to virtualized mixed-criticality real-time systems

A software integration approach for designing and assessing dependable embedded systems

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