Christian Krupitzer

A survey on engineering approaches for self-adaptive systems

The complexity of information systems is increasing in recent years, leading to increased effort for maintenance and configuration. Self-adaptive systems (SASs) address this issue. Due to new computing trends, such as pervasive computing, miniaturization of IT leads to mobile devices with the emerging need for context adaptation. Therefore, it is beneficial that devices are able to adapt context. Hence, we propose to extend the definition of SASs and include context adaptation. This paper presents a taxonomy of self-adaptation and a survey on engineering SASs. Based on the taxonomy and the survey, we motivate a new perspective on SAS including context adaptation.

COMITY: Coordinated application adaptation in multi-platform pervasive systems

Pervasive applications are designed to support users in their daily lives. In order to provide their services, these applications interact with the environment, i.e. their context. They either adapt themselves as a reaction to context changes, or adapt the context via actuators according to their needs. If multiple applications are executed in the same context, interferences are likely to occur. In this paper, we present COMITY-a framework for interference management in multi-platform pervasive systems. Based on contracts specifying an applications interaction with the context, the framework automatically detects interferences and resolves them through a coordinated application adaptation. We analyze the problem of interference resolution, discuss respective algorithms and extensively evaluate our prototype.

Towards Reusability in Autonomic Computing

Reusability of software artifacts reduces development time, effort, and error-proneness. Nevertheless, in the development of autonomic systems, developers often start from scratch when building a new system instead of reusing existing components. Many frameworks offer reusability on a higher level of abstraction, but neglect reusability on the lower component implementation level. In this short paper, we present a reusable adaptation logic by separating the generic structure and mechanisms of Autonomic Computing systems from its custom functionality. That is, we provide a reusable communication architecture with abstract component templates that enables a faster development and easier runtime adaptation. We evaluate our approach in a case study with two implementations.

COMITY: A framework for adaptation coordination in multi-platform pervasive systems

Pervasive applications are designed to support users in their daily lives. In order to provide their services, these applications interact with the environment, i.e., their context. They either adapt themselves as a reaction to context changes, or adapt the context via actuators according to their needs. If multiple applications are executed in the same context, interferences are likely to occur. In this paper, we present COMITY-a framework for interference management in multi-platform pervasive systems. Based on contracts specifying an applications interaction with the context, the framework automatically detects interferences and resolves them through a coordinated application adaptation.

Runtime Evolution of the Adaptation Logic in Self-Adaptive Systems

Self-adaptive systems, which are highly related to Autonomic Computing, are a response to the increasing complexity and size of information systems. They are able to adapt their behavior to changes in the environment or system resources. A self-adaptive system consists of managed resources that realize functionality and an adaptation logic that controls the adaptations. So far, many research has been performed on adapting the managed resources. However, only few works cover adapting the adaptation logic, which might be necessary in several cases, e.g., When the architecture of the managed resources changes. This work adresses why adaptation of the adaptation logic might be beneficial, how it can be achieved, and what challenges arise.

FESAS: Towards a Framework for Engineering Self-Adaptive Systems

The 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.

Fault-avoidance strategies for context-aware schedulers in pervasive computing systems

Scheduling in distributed computing systems is the process of allocating resources to a computational task. The complexity of this allocation process increases with the amount of criteria that are considered for the scheduling decision. Pervasive computing systems show a high degree of heterogeneity and dynamism. The constant joining and leaving of devices makes the system error-prone and less predictable. The involved devices differ in various properties that we subsume as their context. We argue, that these context dimensions can be used to implement fault-avoidant scheduling strategies. In this paper, we introduce the concept of context-aware scheduling for pervasive computing systems. The schedulers in these systems consider multiple context dimensions to avoid failing resource providers. We discuss relevant context dimensions, develop context-aware scheduling strategies and implement them into an existing distributed computing system. We show how to monitor the context dimensions and evaluate the fault-avoidant scheduling strategies in a large-scale simulation.

FESAS IDE: An Integrated Development Environment for Autonomic Computing

While Autonomic Computing can ease the maintenance of systems through adaptations [1], the development of Autonomic Computing systems itself introduces a high complexity. Literature suggests that reusable processes for the development and reusable components in the adaptation logic can reduce the complexity. Existing approaches aim to reduce this complexity with tools and frameworks for specific tasks in the development of the adaptation logic of Autonomic Computing systems. However, to the best of our knowledge, none of these approaches offer an Integrated Development Environment (IDE) for it. In this paper, we extend FESAS - our framework for building reusable adaptation logic components - with Eclipse plug-ins integrated into the FESAS IDE for a simplified development of MAPE components as well as a process for deployment of the components. In this paper, we present these tools. Further, we evaluate their potential to ease the development of self-adaptive systems within five example cases. Last, we discuss the benefits and limitations of the FESAS IDE.

Comparison of Approaches for Self-Improvement in Self-Adaptive Systems

Various trends such as mobility of devices, Cloud Computing, or Cyber-Physical Systems lead to a higher degree of distribution. These systems-of-systems need to be integrated. The integration of various subsystems still remains a challenge. Self-improvement within self-adaptive systems can help to shift integration tasks from the static design time to the runtime, which fits the dynamic needs of these systems. Thus, it can enable the integration of system parts at runtime. In this paper, we define self-improvement as an adaptation of an Autonomic Computing systems adaptation logic. We present an overview of approaches for self-improvement in the domains of Autonomic Computing and self-adaptive systems. Based on a taxonomy for self-adaptation, we compare the approaches and categorize them. The categorization shows that the approaches focus either on structural or parameter adaptation but seldomly combine both. Based on the categorization, we elaborate challenges, that need to be addressed by future approaches for offering self-improving system integration at runtime.

A Dynamic Software Product Line Approach for Adaptation Planning in Autonomic Computing Systems

Modeling the reasoning component of self-adapting systems including its context is a challenging task. Context feature models used in dynamic software product lines help to capture the capabilities of a software as well as the monitored context values. This enables the possibility to add constraints between the context and system features. In this paper, we present an adaptation logic architecture for specifying the knowledge for reasoning in a model-based manner by means of dynamic software product lines. The whole knowledge for reasoning is encapsulated inside a component which enables the reuse of the adaptation logic for various application scenarios. Thus, the system designer only has to specify the adaptation logics knowledge and implement the according interfaces in the managed resource. We evaluate the adaptation logic using our architecture in a distributed computing scenario.