System-scenario-based design of dynamic embedded systems

Abstract

Document VersionPublisher's PDF, also known as Version of Record (includes final page, issue and volume numbers) Please check the document version of this publication:• A submitted manuscript is the author's version of the article upon submission and before peer-review. There can be important differences between the submitted version and the official published version of record. People interested in the research are advised to contact the author for the final version of the publication, or visit the DOI to the publisher's website.• The final author version and the galley proof are versions of the publication after peer review.• The final published version features the final layout of the paper including the volume, issue and page numbers. Link to publicationCitation for published version (APA): Gheorghita, S. V., Palkovic, M., Hamers, J., Vandecappelle, A., Mamagkakis, S., Basten, T., ... Bosschere, . System scenario based design of dynamic embedded systems. (ES reports; Vol. 2007-06). Eindhoven: Technische Universiteit Eindhoven. General rightsCopyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights.• Users may download and print one copy of any publication from the public portal for the purpose of private study or research.• You may not further distribute the material or use it for any profit-making activity or commercial gain • You may freely distribute the URL identifying the publication in the public portal ? Take down policyIf you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. In the past decade, real-time embedded systems have become much more complex due to the introduction of a lot of new functionality in one application, and due to running multiple applications concurrently. This increases the dynamic nature of today's applications and systems, and tightens the requirements for their constraints in terms of deadlines and energy consumption. State-of-theart design methodologies try to cope with these novel issues by identifying several most used cases and dealing with them separately, reducing the newly introduced complexity. This paper presents a generic and systematic design-time/run-time methodology for handling the dynamic nature of modern embedded systems, which can be utilized by existing design methodologies to increase their efficiency. It is based on the concept of system scenarios, which group system behaviors that are similar from a multi-dimensional cost perspective, such as resource requirements, delay, and energy consumption, in such a way that the system can be configured to exploit this cost similarity. At design-time, these scenarios are individually optimized. Mechanisms for predicting the current scenario at run-time and for switching between scenarios are ...

A hierarchical run-time adaptive resource allocation framework for large-scale MPSoC systems

“…Here, we use the concept of scenario [6,22] to capture the application dynamism on our target MPSoC system. There are two different kinds of scenarios: inter-application scenarios describe the simultaneously running applications in the system, while intra-application scenarios define the different execution modes for each application.…”

“…However, these methods typically still suffer from scalability issues when the number of workload scenarios becomes very large as they need to find and store one or more optimal task mappings per scenario at design time (to be used at run time). One solution to address this problem is by reducing the number of workload scenarios by means of clustering [6,27]. However, these methods still suffer from an additional problem of searching for optimal mappings of (clustered) workload scenarios at design time: it should already been known at design time which applications can execute on the target platform.…”

Energy-Aware Resource Allocation in Multi-mode Automotive Applications with Hard Real-Time Constraints

“…This facilitates to identify all the allowed modes and the transitions between them, and to check the cost of mode switchings. In [5], for H.264 decoder, an average switching time overhead between two modes has been measured to be equal to 0.2% of the total system time. This slight value has been caused due to a low number of existing modes, obtained due to the clustering, and thus relatively lower switching.…”

Predictable dynamic embedded data processing

“…The central concept for dealing with dynamic behavior is a scenario [19]. Dynamic behaviors within an application are divided in a limited number of so-called scenarios.…”