Luca Berardinelli

A Development Process for Self-adapting Service Oriented Applications

Software services in the near ubiquitous future will need to cope with variability, as they are deployed on an increasingly large diversity of computing platforms, operate in different execution environments, and communicate through Beyond 3G (B3G) networks. Heterogeneity of the underlying communication and computing infrastructure, physical mobility of platform devices, and continuously evolving requirements claim for services to be adaptable according to the context changes without degrading their quality. Supporting the development and execution of software services in this setting raises numerous challenges that involve languages, methods and tools. However these challenges taken in isolation are not new in the service domain. Integrated solutions to these challenges are the main targets of the IST PLASTIC project. In this paper we introduce the PLASTIC development process model for self-adapting context-aware services, in which we propose model-based solutions to address the main issues of this domain in a comprehensive way. We instantiate the process model by providing methodologies to generate Quality of Service models and adaptable code from UML service models. All these methodologies are supported by an integrated framework which is based on an UML profile that we have defined for the PLASTIC domain.

Performance modeling and analysis of context-aware mobile software systems

Context-awareness is becoming a first class attribute of software systems. In fact, applications for mobile devices need to be aware of their context in order to adapt their structure and behavior and offer the best quality of service even in case the (software and hardware) resources are limited. Although performance is a key non-functional property for such applications, existing approaches for performance modeling and analysis fail to capture the characteristics related to the context, thus resulting not suited for this domain. In this paper we introduce a framework for modeling and analyzing the performance of context-aware mobile software systems. The framework allows to model: the software architecture, the context management, the adaptable behaviors and the performance parameters. Such models can then be transformed into performance models for analysis purposes. We tailor an integrated environment for modeling these elements in UML, and we show how to use it for performance analysis purposes. The modeling environment description and the performance analysis are driven by an example in the eHealth domain.

Model-based co-evolution of production systems and their libraries with AutomationML

System models are essential in planning, designing, realizing, and maintaining production systems. AutomationML (AML) is an emerging standard to represent and exchange heterogeneous artifacts throughout the complete system life cycle and is more and more used as a modeling language. AML is designed as a flexible, prototype-based language able to represent the full spectrum of different artifacts. It may be utilized to build reusable libraries containing prototypical elements to build up production systems by using clones. However, libraries have to evolve over time, e.g., to reflect bug fixes, new features or refactorings, and so system models have to co-evolve to reflect the changes in the libraries. To tackle this co-evolution challenge, we specify in this paper the relationship between library elements, i.e., prototypes, and system elements, i.e., clones, by establishing a formal model for prototype-based modeling languages. Based on this formalization, we introduce several levels of consistency rigor one may want to achieve when modeling with prototype-based languages. These levels are also the main input to reason about the impact of library changes on the concrete system models for which we provide semi-automated co-evolution propagation strategies. We apply the established theory to the concrete AML case and present concrete tool support for evolving AML models based on Eclipse which demonstrates that consistency between system models and libraries may be maintained semi-automatically.

Cross-disciplinary engineering with AutomationML and SysML

Abstract AutomationML (AML) is an emerging standard in the automation domain to represent and exchange artifacts between heterogeneous engineering tools used in different disciplines, such as mechanical and electrical engineering. The Systems Modeling Language (SysML) is a modeling standard influenced by software modeling languages, such as UML, typically adopted in the early phases of engineering processes. This paper investigates commonalities and differences of the structural modeling parts of AML (CAEX) and SysML (block diagrams) in support of establishing tool-independent interoperability. This support for cross-disciplinary modeling is facilitated by a bridge between AML and SysML built on model-driven interoperability techniques. We demonstrate the interoperability between AML and SysML with a case study concerning a lab-sized production system.

Combining fUML and profiles for non-functional analysis based on model execution traces

For developing software systems it is crucial to consider non-functional properties already in an early development stage to guarantee that the system will satisfy its non-functional requirements. Following the model-based engineering paradigm facilitates an early analysis of non-functional properties of the system being developed based on the elaborated design models. Although UML is widely used in model-based engineering, it is not suitable for model-based analysis directly due to its lack of formal semantics. Thus, current model-based analysis approaches transform UML models into formal languages dedicated for analyses purpose, which may introduce accidental complexity of implementing the required model transformations. The recently introduced fUML standard provides a formal semantics of a subset of UML enabling the execution of UML models. In this paper, we show how fUML can be utilized for analyzing UML models directly without having to transform them. We present a reusable framework for performing model-based analyses leveraging execution traces of UML models and integrating UML profiles heretofore unsupported by fUML. A case study in the performance analysis domain is used to illustrate the benefits of our framework.

Modeling and analyzing performance of software for wireless sensor networks

The development of software for Wireless Sensor Networks (WSN) is mostly based on code-and-fix techniques. Up today model-driven engineering techniques have only been limitedly considered in this domain, although they would enable a set of activities aimed at improving the quality of software. In this paper we investigate the possibility to adapt an existing model-based approach that exploits such techniques to combine the modeling and performance analysis of software for WSN. We introduce a UML-based framework where a system model (i) is extended with a new profile for representing NesC application along with the supporting hardware platform, and (ii) is annotated with performance parameters defined in the standard UML MARTE profile. Thereafter we apply a set of transformations to this enhanced UML model that targets a Queueing Network performance model. Finally we illustrate our approach at work on a case study in the agricultural domain.

Energy Consumption Analysis and Design of Energy-Aware WSN Agents in fUML

Wireless Sensor Networks (WSN) are nowadays applied to a wide set of domains (e.g., security, health). WSN are networks of spatially distributed, radio-communicating, battery-powered, autonomous sensor nodes. WSN are characterized by scarcity of resources, hence an application running on them should carefully manage its resources. The most critical resource in WSN is the nodes’ battery.

fUML-Driven Design and Performance Analysis of Software Agents for Wireless Sensor Network

The growing request for high-quality applications for wireless sensor network (wsn) demands model-driven approaches that facilitate the design and the early validation of extra-functional properties by combining design and analysis models. for this purpose, uml and several analysis-specific languages can be chosen and weaved through translational approaches. however, the complexity brought by the underlying technological spaces may hinder the adoption of uml-based approaches in the wsn domain. the recently introduced foundational uml (fuml) standard provides a formal semantics to a strict uml subset, enabling the execution of uml models.

Modeling and Timing Simulation of Agilla Agents for WSN Applications in Executable UML

Wireless Sensor Networks are becoming one of the most successful choices for the development and deployment of a wide range of applications, from intelligent homes to environment monitoring. In response to the growing demand for fast development of WSN applications, we extend an existing UML-based approach for the design and code generation of Agilla applications with functional simulation and timing analysis capabilities through executable UML models. The proposed approach makes use of both a UML profile and an executable model library for Agilla. Execution times, annotated on Agilla instructions and patterns in the library, are given as additional input parameters during the model execution to carry out a timing analysis of the simulated Agilla applications. Modeling and simulation activities rely on MagicDraw© and Cameo Simulation Toolkit©. A running case study is provided to show the approach and the supporting tools at work.

MICE: Monitoring and ModelIng the Context Evolution

Context is an application-specific set of heterogeneous data that a context-aware system should be capable to sense to accordingly adapt its behavior. Context evolution may affect the qualities of the functionalities provided by context-aware systems, in terms of variations of its non-functional properties. In this paper we propose a distributed tool that is capable to monitor, retrieve and arrange heterogeneous data from any IP-enabled device in a set of state-based awareness manager models. The latter are meant to model the context evolution and to be integrated in model-driven approaches to evaluate the impact of the evolution of context on the quality of the provisioned services.