20 research outputs found
Middleware-based system support for proactive adaptation in pervasive environments
No full textPervasive computing applications can adjust their behavior to a multitude of information deemed to be relevant for their situation, their so-called context. Thus far, however, adaptation in such context-aware systems is reactive and limited to the application itself. These restrictions inevitably delay adjustments to events. They cause frequent reconfigurations, and may result in inferior overall system configurations. In this paper, we present our work in progress on middleware-based system support for proactive adaptation. It offers context information, prediction, and influence via a uniform abstraction, update notifications for subscribed context or predictions, and an application model to determine adaptation alternatives
System support for proactive adaptation
No full textApplications in our modern, pervasive computing environments have to adapt themselves or their context in order to cope with changes. In the process, these pervasive applications should be as unobtrusive as possible, i.e., their adaptation should be automatic. In dynamic multi-user systems with shared resources and interactive applications, such adaptations cannot be scripted in advance. Instead, they have to be calculated at runtime. However, the necessary calculations quickly exceed the complexity that can be handled in real-time, i.e., without causing significant delays. The concept of proactive adaptation allows to change applications and/or context based on prediction of context and user behavior. Hence, proactive adaptation can reduce adaptation delays and avoid context interferences by determining coordinated adaptation plans ahead of time, instead of reactively when adaptation becomes necessary. Further, it helps to provide a seamless service to the user, while optimizing the overall system utility.
This thesis presents a general framework and middleware-based system support for coordinated proactive adaptation in dynamic multi-user pervasive systems. The framework consists of five major components. The context interaction model and corresponding context broker offers context information, prediction, as well as actuation in a uniform fashion. The application configuration model allows applications to specify their requirements towards their context, as well as detail user preferences and duration-dependent utility and cost functions for adaptation optimization. Configuration algorithms calculate and rate all adaptation alternatives of an application given a current or predicted context and the specified rating functions, before coordination algorithms find interference-free adaptation plans for situations in which multiple applications share a context space. Finally, the adaptation control component combines the individual components of the framework in a two-dimensional control loop for proactive and fallback reactive adaptation. The prototype framework is evaluated in real-time simulations of an interactive pervasive system using recorded user traces
FESAS: Towards a Framework for Engineering Self-Adaptive Systems
No full textThe complexity and size of information systems are growing, resulting in an increasing effort for maintenance. Self-adaptive systems (SAS) that autonomously adapt to changes in the environment or in the system itself (e.g. disfunction of components) can be a solution. So far, the development of SAS is frequently tailored to specific use case requirements. The creation of frameworks with reusable process elements and system components is often neglected. However, with such a framework developing SAS would become faster and less error prone. This work addresses this gap by providing a framework for engineering SAS
Configuration Management for Proactive Adaptation in Pervasive Environments
No full textPervasive computing applications have to adapt in order to cope with changes in their environment. Proactive adaptation allows to change the application and/ or the context based on prediction of context and user behavior, in order to reduce adaption delay and provide a seamless service to the user. Thus, such applications are self-organizing systems. Ideally, self-organizing systems adapt by changing their structure or behavior without requiring the user's intervention. A prerequisite to that is the knowledge of the possible configurations and their order with respect to the suitability. We introduce a comprehensive framework based on an application model with suitability and cost metrics. Based on the application model, we construct a CSP and develop an algorithm with two heuristics that finds all configurations. We rate the configurations depending on their expected instantiation using novel utility and cost functions. In the evaluation, we show the feasibility of our approach
PriMe : human-centric privacy measurement based on user preferences towards data sharing in mobile participatory sensing systems
No full textDepartment of Computin
