3,686 research outputs found
Recommended from our members
Efficient Memory-Protected Integration of Add-On Software Subsystems in Small Embedded Automotive Applications
Current innovations in the automotive industry
evolve mainly in the electronics and software domain. This leads
to an increasing integration of additional software subsystems
into already existing electronic control units (ECUs) to cope with
the raised amount and complexity of present ECUs in modern
high-end vehicles. This paper discusses different approaches
which are required to integrate such add-on software subsystems
in an isolated memory domain, and considers particularly the
special needs of small embedded systems—including the limited
hardware support. Special focus is brought to the efficient detection
of malicious memory accesses, as well as the benefits of
a thereupon possible and adaptable failure-handling strategy.
All investigations are based on a developed memory-protection
framework which has been tailored to the special needs of a sample
vehicle dynamics control system. Its usage allows the combination
of. integrating additional subsystems without reducing the main
application’s availability
Context-aware adaptation in DySCAS
DySCAS is a dynamically self-configuring middleware for automotive control systems. The addition of autonomic, context-aware dynamic configuration to automotive control systems brings a potential for a wide range of benefits in terms of robustness, flexibility, upgrading etc. However, the automotive systems represent a particularly challenging domain for the deployment of autonomics concepts, having a combination of real-time performance constraints, severe resource limitations, safety-critical aspects and cost pressures. For these reasons current systems are statically configured. This paper describes the dynamic run-time configuration aspects of DySCAS and focuses on the extent to which context-aware adaptation has been achieved in DySCAS, and the ways in which the various design and implementation challenges are met
Composition and Self-Adaptation of Service-Based Systems with Feature Models
The adoption of mechanisms for reusing software in pervasive systems has not yet become standard practice. This is because the use of pre-existing software requires the selection, composition and adaptation of prefabricated software parts, as well as the management of some complex problems such as guaranteeing high levels of efficiency and safety in critical domains. In addition to the wide variety of services, pervasive systems are composed of many networked heterogeneous devices with embedded software. In this work, we promote the safe reuse of services in service-based systems using two complementary technologies, Service-Oriented Architecture and Software Product Lines. In order to do this, we extend both the service discovery and composition processes defined in the DAMASCo framework, which currently does not deal with the service variability that constitutes pervasive systems. We use feature models to represent the variability and to self-adapt the services during the composition in a safe way taking context changes into consideration. We illustrate our proposal with a case study related to the driving domain of an Intelligent Transportation System, handling the context information of the environment.Work partially supported by the projects TIN2008-05932,
TIN2008-01942, TIN2012-35669, TIN2012-34840 and CSD2007-0004 funded by
Spanish Ministry of Economy and Competitiveness and FEDER; P09-TIC-05231 and
P11-TIC-7659 funded by Andalusian Government; and FP7-317731 funded by EU. Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec
Lifecycle Management of Automotive Safety-Critical Over the Air Updates: A Systems Approach
With the increasing importance of Over The Air (OTA) updates in the automotive field, maintaining safety standards becomes more challenging as frequent incremental changes of embedded software are regularly integrated into a wide range of vehicle variants. This necessitates new processes and methodologies with a holistic view on the backend, where the updates are developed and released
Kuksa*: Self-Adaptive Microservices in Automotive Systems
In pervasive dynamic environments, vehicles connect to other objects to send
operational data and receive updates so that vehicular applications can provide
services to users on demand. Automotive systems should be self-adaptive,
thereby they can make real-time decisions based on changing operating
conditions. Emerging modern solutions, such as microservices could improve
self-adaptation capabilities and ensure higher levels of quality performance in
many domains. We employed a real-world automotive platform called Eclipse Kuksa
to propose a framework based on microservices architecture to enhance the
self-adaptation capabilities of automotive systems for runtime data analysis.
To evaluate the designed solution, we conducted an experiment in an automotive
laboratory setting where our solution was implemented as a microservice-based
adaptation engine and integrated with other Eclipse Kuksa components. The
results of our study indicate the importance of design trade-offs for quality
requirements' satisfaction levels of each microservices and the whole system
for the optimal performance of an adaptive system at runtime
Developing a distributed electronic health-record store for India
The DIGHT project is addressing the problem of building a scalable and highly available information store for the Electronic Health Records (EHRs) of the over one billion citizens of India
- …