Erlend Stav

Using architecture models for runtime adaptability

Every software system has architecture. The architecture strongly influences the software systems properties, including maintainability and runtime properties such as performance and reliability. By describing the architecture in models, we can make the architecture explicit. Developers typically use software architecture models at design time to capture the significant decisions about a software systems organization and to describe and establish a common understanding about the systems abstract properties. In the MADAM (mobility- and adaptation-enabling middleware) project, we aim to facilitate adaptive application development for mobile computing. We follow an architecture-centric approach where we represent architecture models at runtime to allow generic middleware components to reason about and control adaptation.

Using product line techniques to build adaptive systems

Adaptive systems are able to adapt their properties and resource requirements at runtime in response to dynamically varying user needs and resource constraints. With the emergence of mobile and service oriented computing, such variation is becoming increasingly common, and the need for adaptivity is increasing accordingly. Software product line engineering has proved itself as an efficient way to deal with varying user needs and resource constraints. In this paper we present an approach to building adaptive systems based on product line oriented techniques such as variability modeling and component based architectures. By representing the product line architecture at runtime, we are able to delegate much of the complexity of adaptation to a reusable adaptation platform. To validate our approach we have built a prototype adaptation platform and developed a few pilot applications exploiting the platform to achieve adaptivity.

Composing components and services using a planning-based adaptation middleware

Self-adaptive component-based architectures provide methods and mechanisms to support the dynamic adaptation of their structure under evolving execution context. Dynamic adaptation is particularly relevant in the domain of ubiquitous computing, which is subject to numerous unexpected changes of the execution context. In this paper, we focus on changes in the service provider landscape: business services may dynamically come and go, and their quality of service may vary. We introduce an extension of the MADAM component-based planning framework that optimizes the overall utility of applications when such changes occur. MADAM planning is based on dynamic configuration of component frameworks. The extended planning framework supports seamless configuration of component frameworks based on both local and remote components and services. In particular, components and services can be plugged in interchangeably to provide functionalities defined by the component framework. The extended planning framework is illustrated and validated on a use case scenario.

Model-based user interface adaptation

Most work on model-based cross-platform user interface development is based on an assumption that the user interfaces on the different platforms should be as similar as possible. Much work on mobile user interfaces claim the opposite A¢â‚¬â€œ that user interfaces on a mobile platform should have features not applicable on a stationary one and vise versa. Exploiting contextual information in user interfaces on mobile equipment is a prime example of this. This paper focus on this dichotomy between common development and exploiting platform specific features (or having specialized versions) on each platform. Few or none of the existing model-based languages and tools for user interface development are able to combine these two needs. These aspects are initially very difficult to combine, but in the paper we present an approach that makes this possible. First we briefly present our modelling approach, we pinpoint some of the general differences between mobile and stationary user interfaces, and we present an approach to building such self adapting systems where the adaptation is handled by generic middleware. Our approach builds on component frameworks and variability engineering to achieve adaptable systems, and property modelling, architectural reflection and context monitoring to support dynamic self-adaptation. With this as a background we investigate how the presented modelling approach may be extended and combined with the adaptive architecture to facilitate mode l-based user interface adaptation. Finally, we present some more general principles for how model-based approaches may be used when developing adaptive user interfaces.

Distributed context management in a mobility and adaptation enabling middleware (MADAM)

As computing devices are getting smaller, we tend to bring them everywhere. Consequently the operating conditions of the devices are constantly changing (e.g. changing user requirements, change in the system context and environment context). In order to be usable and dependable, applications and services need to self-adapt to changes in context. This work describes a context management approach for reducing the complexity of context aggregation and utilisation. The context manager is a core component in the MADAM (Mobility and ADaptation enAbling Middleware) project.

Experiences from Model-Driven Development of Homecare Services: UML Profiles and Domain Models

Model-driven development approaches such as Model Driven Architecture (MDA) have been proposed as the new paradigm for software development. The adoption of MDA is still low, partly because of the general-purpose modelling language being used. Domain specific modelling languages are being developed for technological and industrial domains to improve the expressiveness and effect of model-driven development techniques. The healthcare domain could benefit from these methodologies. In order to incorporate domain knowledge in a MDA process, information about workflows, artefacts and actors can be formalized in a UML profile and applied by MDA tools for design and development. This paper presents the work done on model-driven development of smart homecare services in the MPOWER project. Following an iterative approach, two UML profiles to support development of Service Oriented Architecture based homecare applications are proposed. Using homecare specific UML profiles indicate an improvement in the process for model-driven development of homecare services.

A middleware centric approach to building self-adapting systems

The use of handheld networked devices to access information systems by people moving around is spreading rapidly. Systems being used in this way typically face dynamic variation in their operating environment. This poses new challenges for system developers that need to build systems that adapt dynamically to the changing operating environment in order to maintain usability and usefulness for mobile users. In this paper we propose an approach to building such self-adapting systems where the adaptation is handled by generic middleware. Our approach builds on component frameworks and variability engineering to achieve adaptable systems, and property modelling, architectural reflection and context monitoring to support dynamic self-adaptation.

Self-adaptation for everyday systems

The use of handheld networked devices to access information systems by people moving around is spreading rapidly. Systems being used in this way typically face dynamic variation in their operating environment. In order to maintain the usability and usefulness for mobile users, self-adapting systems are needed. Self-adaptation has so far typically been applied only to mission critical systems at considerable additional cost. However, we now need ways to implement such capabilities that are affordable also in everyday systems development.In this paper we propose an approach to building such self-adapting systems where the adaptation is handled by generic middleware. The proposed approach builds on component frameworks and variability engineering to achieve adaptable systems, and property modelling, architectural reflection and context monitoring to support dynamic self-adaptation. We define a set of requirements for affordable self-adaptation and discuss the proposed approach in relation to these requirements.

CloudScale: scalability management for cloud systems

This work-in-progress paper introduces the EU FP7 STREP CloudScale. The contribution of this paper is an overall description of CloudScales engineering approach for the design and evolution of scalable cloud applications and services. An Electronic Health Record (EHR) system serves as a motivation scenario. The overall CloudScale method describes how CloudScale will identify and gradually solve scalability problems in this existing applications. CloudScale will also enable the modelling of design alternatives and the analysis of their effect on scalability and cost. Best practices for scalability will further guide the design process. The CloudScale method is supported by three integrated tools and a scalability description modelling language. CloudScale will be validated by two case studies.

Interfering effects of adaptation: implications on self-adapting systems architecture

When people are moving around using handheld networked devices, the environment for the provided services vary influencing service quality properties and user needs. In order to maintain usability and usefulness for mobile users, dynamic service adaptation is needed. Several forms of adaptation may be applied. For example, the application structure may adapt from thin client to self-reliant client, or network handover may be performed. The selection of an adaptation type is however far from obvious. Adaptation usually has impact on system resources or service quality. Also, one adaptation may require other adaptations that again have impact on resources and quality. This paper illustrates the complexity of selecting an adequate adaptation form. We argue that adaptation selection requires advanced reasoning and identify implications on the architecture of self-adapting systems.