Dependability Driven Integration of Mixed Criticality SW Components

Islam, S.M.R.; Lindström, Rasmus; Suri, Neeraj

doi:10.1109/isorc.2006.26

Cited by 19 publications

(24 citation statements)

References 15 publications

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“…Especially, the evaluation of the different quality concerns of a system in relation to its architectural aspects, such as a specific deployment configuration, is of paramount importance and it should be performed as early as at modeling level. There are a number of model-driven approaches that provide ways to model specific quality attributes and push them to the software level (Islam et al 2006;Grunske et al 2007). Zhu et al (2012) present model-driven mechanisms for the optimization of task allocation, signal to message mapping, and assignment of priorities to tasks and messages in order to meet end-to-end deadline constraints and minimise latencies.…”

Section: Related Workmentioning

confidence: 99%

Architecture optimization: speed or accuracy? both!

et al. 2016

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Embedded systems are becoming more and more complex, thus demanding innovative means to tame their challenging development. Among others, early architecture optimization represents a crucial activity in the development of embedded systems to maximise the usage of their limited resources and to respect their real-time requirements. Typically, architecture optimization seeks good architecture candidates based on model-based analysis. Leveraging abstractions and estimates, this analysis usually produces approximations useful for comparing architecture candidates. Nonetheless, approximations do not provide enough accuracy in estimating crucial extra-functional properties. In this article, we provide an architecture optimization framework that profits from both the speed of model-based predictions and the accuracy of execution-based measurements. Model-based optimization rapidly finds a good architecture candidate, which is refined through optimization based on monitored executions of automatically generated code. Moreover, the framework enables the developer to leverage her optimization experience. More specifically, the developer can use runtime monitoring of generated code execution to manually adjust task allocation at modeling level, and commit the changes without halting execution. In the article, our architecture optimization mechanism is first described from a general point of view and then exploited for optimizing the allocation of software tasks to the processing cores of a multicore embedded system; we target extra-functional properties that can be

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Section: Related Workmentioning

confidence: 99%

Architecture optimization: speed or accuracy? both!

et al. 2016

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“…For the model-based approaches, different quality evaluation techniques have been used, implied by the models used for specific quality attributes. As an example reliability block diagrams [57], [58], [63], [121], [136], [137], [149], [208], [217], discrete-time Markov chains [61], [96], [97], [165], [232], and fault trees [67], [184], [199] are used for reliability; queuing networks [35], [80], [143], [144], [168], [169], [171], [245], execution graphs [85], [107], [115], and discrete-time Markov chains [210] are used to evaluate performance; fault trees [8], [180], [184], [185], [201], [223] and binary decision diagrams [8], [185] are used for safety evaluation; continuous-time Markov chains [193], Markov decision processes [212], Petri-nets [194], and Markov reward models [165] are used for evaluation of a system's energy consumption. Quantitative metrics of the quality attributes are obtained by either mathematically analyzing or simulating the models.…”

Section: Mts(2)mentioning

confidence: 99%

Software Architecture Optimization Methods: A Systematic Literature Review

Aleti

Bühnová

Grunske

et al. 2013

IIEEE Trans. Software Eng.

237

146

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Due to significant industrial demands toward software systems with increasing complexity and challenging quality requirements, software architecture design has become an important development activity and the research domain is rapidly evolving. In the last decades, software architecture optimization methods, which aim to automate the search for an optimal architecture design with respect to a (set of) quality attribute(s), have proliferated. However, the reported results are fragmented over different research communities, multiple system domains, and multiple quality attributes. To integrate the existing research results, we have performed a systematic literature review and analyzed the results of 188 research papers from the different research communities. Based on this survey, a taxonomy has been created which is used to classify the existing research. Abstract-Due to significant industrial demands toward software systems with increasing complexity and challenging quality requirements, software architecture design has become an important development activity and the research domain is rapidly evolving. In the last decades, software architecture optimization methods, which aim to automate the search for an optimal architecture design with respect to a (set of) quality attribute(s), have proliferated. However, the reported results are fragmented over different research communities, multiple system domains, and multiple quality attributes. To integrate the existing research results, we have performed a systematic literature review and analyzed the results of 188 research papers from the different research communities. Based on this survey, a taxonomy has been created which is used to classify the existing research. Furthermore, the systematic analysis of the research literature provided in this review aims to help the research community in consolidating the existing research efforts and deriving a research agenda for future developments.

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“…A set of constraints need to be satisfied for a mapping to be valid [16]. We consider the following constraints: (i) binding constraints -jobs that need to be allocated onto specific nodes due to the need of certain resources (e.g., sensors or actuators), (ii) FT constraints -separation of replicas to different nodes, (iii) schedulability -maintaining RT constraints and (iv) computing constraints -such as the amount of memory available for jobs.…”

Section: Hw Modelmentioning

confidence: 99%

“…Mapping algorithms need heuristics to achieve good performance. Of particular importance are job ordering and node ordering that decide which job to assign next and what node to assign that job onto [16]. Job and node ordering are described in Step 4.…”

Section: The Mvo Approachmentioning

confidence: 99%

See 1 more Smart Citation

A Multi Variable Optimization Approach for the Design of Integrated Dependable Real-Time Embedded Systems

Islam

Suri

Embedded and Ubiquitous Computing

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Abstract. Embedded systems increasingly encompass both dependability and responsiveness requirements. While sophisticated techniques exist, on a discrete basis, for both dependability/fault-tolerance (FT) and real-time (RT), the composite considerations for FT+RT are still evolving. Obviously the different objectives needed for FT and RT make composite optimization hard. In this paper, the proposed Multi Variable Optimization (MVO) process develops integrated FT+RT considerations. We introduce dependability as an initial optimization criteria by confining error propagation probability, i.e., limiting the interactions. Subsequently, quantification of interactions together with RT optimization by minimizing scheduling length is developed. A simulated annealing approach is utilized to find optimized solutions. We provide experimental results for our approach, showing significant design improvements over contemporary analytical initial feasibility solutions.

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Dependability Driven Integration of Mixed Criticality SW Components

Cited by 19 publications

References 15 publications

Architecture optimization: speed or accuracy? both!

Architecture optimization: speed or accuracy? both!

Software Architecture Optimization Methods: A Systematic Literature Review

A Multi Variable Optimization Approach for the Design of Integrated Dependable Real-Time Embedded Systems

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