JSON Schemas with Semantic Annotations Supporting Data Translation

As service-oriented architectures are a solution for large distributed systems, interoperability between these systems, which are often heterogeneous, can be a challenge due to the different syntax and semantics of the exchanged messages or even different data interchange formats. This paper addresses the data interchange format and data interoperability issues between XML-based and JSON-based systems. It proposes novel annotation mechanisms to add semantic annotations and complement date values to JSON Schemas, enabling an interoperability approach for JSON-based systems that, until now, was only possible for XML-based systems. A set of algorithms supporting the translation from JSON Schema to XML Schema, JSON to XML, and XML to JSON is also proposed. These algorithms were implemented in an existing prototype tool, which now supports these systems’ interoperability through semantic compatibility verification and the automatic generation of translators.

Model-based resource analysis and synthesis of service-oriented automotive software architectures

Context Automotive software architectures describe distributed functionality by an interaction of software components. One drawback of today’s architectures is their strong integration into the onboard communication network based on predefined dependencies at design time. The idea is to reduce this rigid integration and technological dependencies. To this end, service-oriented architecture offers a suitable methodology since network communication is dynamically established at run-time. Aim We target to provide a methodology for analysing hardware resources and synthesising automotive service-oriented architectures based on platform-independent service models. Subsequently, we focus on transforming these models into a platform-specific architecture realisation process following AUTOSAR Adaptive. Approach For the platform-independent part, we apply the concepts of design space exploration and simulation to analyse and synthesise deployment configurations, i. e., mapping services to hardware resources at an early development stage. We refine these configurations to AUTOSAR Adaptive software architecture models representing the necessary input for a subsequent implementation process for the platform-specific part. Result We present deployment configurations that are optimal for the usage of a given set of computing resources currently under consideration for our next generation of E/E architecture. We also provide simulation results that demonstrate the ability of these configurations to meet the run time requirements. Both results helped us to decide whether a particular configuration can be implemented. As a possible software toolchain for this purpose, we finally provide a prototype. Conclusion The use of models and their analysis are proper means to get there, but the quality and speed of development must also be considered.

Software architectures in smart manufacturing: Review and experiences

Cyber-physical systems based on heterogeneous and distributed devices, applications and services are the core of smart factories. Smart manufacturing systems are highly dependent on software applications and services that enable integration of data from different and heterogeneous sources, as well as support for control and management processes. Development and implementation of specific architecture styles and patterns in smart industrial settings is essential for their performance. Several software architecture styles used in Industry 4.0 environments are discussed and illustrated with examples from literature. Our experience with a prototype of a smart sensor-based layered architecture is presented and discussed. Further work will be directed towards development of service oriented architectures and reengineering method for old fashioned industrial settings.

A Two Phases Self-healing Framework for Service-oriented Systems

Service-Oriented Architectures (SOA) enable the automatic creation of business applications from independently developed and deployed Web services. As Web services are inherently a priori unknown, how to deliver reliable Web services compositions is a significant and challenging problem. Services involved in an SOA often do not operate under a single processing environment and need to communicate using different protocols over a network. Under such conditions, designing a fault management system that is both efficient and extensible is a challenging task. In this article, we propose SFSS, a self-healing framework for SOA fault management. SFSS is predicting, identifying, and solving faults in SOAs. In SFSS, we identified a set of high-level exception handling strategies based on the QoS performances of different component services and the preferences articled by the service consumers. Multiple recovery plans are generated and evaluated according to the performance of the selected component services, and then we execute the best recovery plan. We assess the overall user dependence (i.e., the service is independent of other services) using the generated plan and the available invocation information of the component services. Due to the experiment results, the given technique enhances the service selection quality by choosing the services that have the highest score and betters the overall system performance. The experiment results indicate the applicability of SFSS and show improved performance in comparison to similar approaches.

Robotic Systems of Systems Based on a Decentralized Service-Oriented Architecture

Multi-robot systems are often static and pre-configured during the design time of their software. Emerging cooperation between unknown robots is still rare and limited. Such cooperation might be basic like sharing sensor data or complex like conjoined motion planning and acting. Robots should be able to detect other robots and their abilities during runtime. When cooperation seems to be possible and beneficial, it should be initiated autonomously. A centralized cloud control shall be avoided. Using software patterns belonging to service-oriented architectures, the robots are able to discover other robots and their abilities during runtime. These abilities are implemented as services and described by their interfaces. Composition of services can be done easily and flexibly. The software patterns originally belonging to cloud computing could be successfully adopted to decentralized multi-robot systems. The developed concept allows autonomous systems to cooperate flexibly and to compose multi-robot systems during runtime.