Abstract: An important emerging requirement for computing systems is the ability to adapt at run time, taking advantage of local computing devices, and coping with dynamically changing resources. Three specific technical challenges in satisfying this requirement are to (1) select an appropriate set of applications or services to carry out a user s task, (2) allocate (possibly scarce) resources among those applications, and (3) reconfigure the applications or resource assignments if the situation changes. In this paper we show how to provide a shared infrastructure that automates configuration decisions given a specification of the user s task. The heart of the approach is an analytical model and an efficient algorithm that can be used at run time to make near-optimal (re)configuration decisions. We validate this approach both analytically and by applying it to a representative scenario.

Abstract: 'Time is money', or so goes the old saying. Perhaps influenced by this aphorism, some strategies for incorporating costs in the analysis of software design express all costs in currency units for reasons of simplicity and tractability. Indeed, in theoretical economics all costs can, in principle, be expressed in dollars. Software engineering problems, however, often present situations in which converting all costs to a common currency is problematical. In this paper we pinpoint some of these situations and the underlying causes of the problems, and we argue that it is often better to treat costs as a multidimensional value, with dimensions corresponding to distinct types of resources. We go on to highlight the differences among cost dimensions that need to be considered when developing cost-benefit analyses, and we suggest mechanisms for mediating among heterogeneous cost dimensions.

Abstract: Addressing resource variation plays an increasingly important role in engineering today’s software sys- tems. Research in resource-adaptive applications takes an important step towards addressing this problem. However, existing solutions stop short of addressing the fact that different user tasks often have specific goals of quality of service, and that such goals often entail multiple aspects of quality of service. This paper presents a framework for engineering software systems capable of adapting to resource variations in ways that are specific to the quality goals of each user task. For that, users are empowered to specify their task-specific preferences with respect to multiple aspects of quality of service. Such prefer- ences are then exploited to both coordinate resource usage across the applications supporting the task, and to dynamically control the resource adaptation polices of those applications. A user study validates that non-expert users can use our framework to successfully control the behavior of such adaptive systems.