Tanguy Le Berre, P. Mauran, G. Padiou, P. Quéinnec
{"title":"Real time behavior of data in distributed embedded systems","authors":"Tanguy Le Berre, P. Mauran, G. Padiou, P. Quéinnec","doi":"10.1109/IMCSIT.2008.4747300","DOIUrl":null,"url":null,"abstract":"Nowadays, most embedded systems become distributed systems structured as a set of communicating components. Therefore, they display a less deterministic global behavior than centralized systems and their design and analysis must address both computation and communication scheduling in more complex configurations. We propose a modeling framework centered on data. More precisely, the interactions between the data located in components are expressed in terms of a so-called observation relation. This abstraction is a relation between the values taken by two variables, the source and the image, where the image gets past values of the source. We extend this abstraction with time constraints in order to specify and analyze the availability of timely sound values. The formal description of the observation-based computation model is stated using the formalisms of transition systems. Real time is introduced as a dedicated variable. As a first result, this approach allows to focus on specifying time constraints attached to data and to postpone task and communication scheduling matters. At this level of abstraction, the designer has to specify time properties about the timeline of data such as their freshness, stability, latency... As a second result, a verification of the global consistency of the specified system can be automatically performed. A forward or backward approach can be chosen. The verification process can start from either the timed properties (e.g. the period) of data inputs or the timed requirements of data outputs (e.g. the latency). As a third result, communication protocols and task scheduling strategies can be derived as a refinement towards an actual implementation.","PeriodicalId":267715,"journal":{"name":"2008 International Multiconference on Computer Science and Information Technology","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 International Multiconference on Computer Science and Information Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IMCSIT.2008.4747300","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Nowadays, most embedded systems become distributed systems structured as a set of communicating components. Therefore, they display a less deterministic global behavior than centralized systems and their design and analysis must address both computation and communication scheduling in more complex configurations. We propose a modeling framework centered on data. More precisely, the interactions between the data located in components are expressed in terms of a so-called observation relation. This abstraction is a relation between the values taken by two variables, the source and the image, where the image gets past values of the source. We extend this abstraction with time constraints in order to specify and analyze the availability of timely sound values. The formal description of the observation-based computation model is stated using the formalisms of transition systems. Real time is introduced as a dedicated variable. As a first result, this approach allows to focus on specifying time constraints attached to data and to postpone task and communication scheduling matters. At this level of abstraction, the designer has to specify time properties about the timeline of data such as their freshness, stability, latency... As a second result, a verification of the global consistency of the specified system can be automatically performed. A forward or backward approach can be chosen. The verification process can start from either the timed properties (e.g. the period) of data inputs or the timed requirements of data outputs (e.g. the latency). As a third result, communication protocols and task scheduling strategies can be derived as a refinement towards an actual implementation.