Modeling and efficient solving of extra-functional properties for adaptation in networked embedded real-time systems

Zeller, Marc; Prehofer, Christian

doi:10.1016/j.sysarc.2012.11.003

Cited by 17 publications

(8 citation statements)

References 31 publications

(27 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Another line of research addresses the self‐healing of the distributed systems by the automatic redeployment of software to hardware. () These approaches use a model of the hardware nodes and buses in the system, including their properties (eg, memory, type of processors, sensors) and a model of the software components, including their connections and their requirements to compute a deployment from components to hardware nodes. If a hardware node fails, a new deployment is computed to ensure that all software components are running again.…”

Section: State Of the Artmentioning

confidence: 99%

“…While our own previous work and the work of Zeller and Prehofer only compute the new deployment, Klöpper et al additionally support the computation of self‐healing plans as an ordered sequence of self‐healing actions (eg, loading the code of a software component to a hardware node, starting a software component, connecting, and disconnecting software components).…”

Section: State Of the Artmentioning

confidence: 99%

See 1 more Smart Citation

Industrial experiences from evolving measurement systems into self‐healing systems for improved availability

et al. 2017

View full text Add to dashboard Cite

Automated measurement programs are an efficient way of collecting, processing, and visualizing measures in large software development companies. The number of measurements in these programs is usually large, which is caused by a diversity of the needs of the stakeholders. In this paper, we present the application of the self-healing concepts to assure the availability of measurements to the stakeholders without the need for effort-intensive and costly manual interventions of the operators. We study the measurement infrastructure at one of the development units of a large infrastructure provider. In this paper, we present how the Monitor, Analyze, Plane, and Execute with Knowledge model was instantiated in a simplistic manner to reduce the need for manual intervention in the operation of the measurement systems. Based on the experiences from the 2 cases studied in this paper, we show how an evolution toward self-healing measurement systems is done both with a dedicated failure taxonomy and with an effective straightforward handling of the most common errors in the execution.The mechanisms studied and presented in this paper show that self-healing provides significant improvements to the operation of the measurement program and reduces the need for daily oversight by an operator for the measurement systems.KEYWORDS measurement systems, metrics, self-healing INTRODUCTIONModern software development organizations utilize software measurement to get insight into the performance of their products or efficiency of the organization, which over time leads companies to collect a large amount of measurement data. The growing amount of measurement data leads to a growing effort for maintaining the measurement program. The needs in such large organizations and their evolution entail the need to constantly monitor and repair measurement systems. One of the challenges is to balance the availability of the measurements and with the cost of operating the measurement program. The availability of the measurement systems is required to support the operations of the company and to improve its decisions; the up-to-date information should be available, and if it is not up-to-date, its latest status should be provided and the user (stakeholder) of the information notified.

show abstract

Section: State Of the Artmentioning

confidence: 99%

Section: State Of the Artmentioning

confidence: 99%

Industrial experiences from evolving measurement systems into self‐healing systems for improved availability

et al. 2017

View full text Add to dashboard Cite

show abstract

“…The focus in that paper is on what impact that different architectural solutions will have on the ability to evolve the system. Specific solutions have also been proposed for handling evolution (see for example [15][16] [17]) but additional focus on the entire system architecture including both software and hardware is needed.…”

Section: Related Workmentioning

confidence: 99%

A method for handling evolvability in a complex embedded system

Hallmans

Nolte

Larsson

2013

2013 IEEE 18th Conference on Emerging Technologies &Amp; Factory Automation (ETFA)

View full text Add to dashboard Cite

Handling of obsolete software and/or hardware components together with management of function updates in a complex embedded system with an expected life time of more than 30 years can be a very difficult to almost impossible task. This types of challenges can be found in a large number of companies in, for example, the power transmission industry, power plants, aviation etc. In this paper we present the basic steps in a proposed method for handling evolvability in such embedded systems with long expected life cycles. The key elements of the proposed method are the definition of function dependencies, release planning, and test requirements.

show abstract

“…There is a vast body of publications on applying DSE methods to solve this resource allocation problem. These publications try to improve the DSE methods mainly in three directions; the calculation efficiency of the exploration [17,19,20,15,18], the optimality of the suggested design decisions [19,18] and the generality of the DSE process. Generality here can be interpreted as the realism of the assumptions, the adaptability to different use cases and the convenience for the users.…”

Section: Introductionmentioning

confidence: 99%

Formulating customized specifications for resource allocation problem of distributed embedded systems

Zhang

Feng

Törngren

et al. 2016

Proceedings of the 35th International Conference on Computer-Aided Design

View full text Add to dashboard Cite

There are plentiful attempts for increasing the efficiency, generality and optimality of the Design Space Exploration (DSE) algorithms for resource allocation problems of distributed embedded systems. Most contemporary approaches formulate DSE as an optimization or SAT problem, based on a set of predefined constraints. In this way, the end users lose the flexibility to guide and customize the exploration based on specifics of their actual problem. Besides, during the design of the DSE algorithms, manual formulation is time consuming and error-prone. To solve these problems, 1) a formal representation is defined for capturing customized architectural constraints based on a combination of propositional logic and Pseudo-Boolean (PB) formulas; 2) A process is designed to automatically translate these architectural constrains into corresponding Integer Linear Programming (ILP) constraints, commonly used for DSE. The translation process is also optimized to create ILP formulation with less introduced variables so as to reduce computation time. The results show that the generated constraints correctly reflect the corresponding specification with decent efficiency.

show abstract

Modeling and efficient solving of extra-functional properties for adaptation in networked embedded real-time systems

Cited by 17 publications

References 31 publications

Industrial experiences from evolving measurement systems into self‐healing systems for improved availability

Industrial experiences from evolving measurement systems into self‐healing systems for improved availability

A method for handling evolvability in a complex embedded system

Formulating customized specifications for resource allocation problem of distributed embedded systems

Contact Info

Product

Resources

About