Dirk Niebuhr

Engineering of IT ecosystems: design of ultra-large-scale software-intensive systems

Ultra-Large-Scale Systems are considered to be the new system generation. For these systems current development approaches are not well suited, since they do not scale well for large systems. One view onto such systems is to see them as IT Ecosystems comparable to complex ecosystems from nature and biology. We will present an example for such a system, the smart city. Furthermore, we will present challenges that arise from engineering and operating IT Ecosystems.

A component model for dynamic adaptive systems

Dynamic adaptive systems are systems which change their behavior according to the needs of the user during runtime based on context information. Since it is not feasible to develop these systems from scratch every time, a component model enabling dynamic adaptive systems is necessary. Moreover, an infrastructure is required which is capable of wiring dynamic adaptive systems from a set of components in order to provide a dynamic and adaptive behavior to the user. In this paper we present such kind of infrastructure called DAiSI (Dynamic Adaptive System Infrastructure) and the underlying component model. We will present an example scenario illustrating the adaptation capabilities of the introduced component model.

Application of the v-modell XT – report from a pilot project

The new V-Modell XT has replaced the well-known V-Modell 97 as obligatory development process standard IT-projects of Germany’s government and military service. During the development of the V-Modell XT a wide Beta-test phase was planned, enabling the project partners to make first experiences in practical use. Furthermore, the pilot projects enable all participants to come closer to the new standard and learn more about its strengths and weaknesses. After having a short look at the new concepts of the V-Mo dell XT, we present some experiences made during the pilot project “Development of the WiBe software” for the German Department of the Interior. We will present some experiences we made and provide some quantitative data of products created during the project.

Achieving Dependable Component Bindings in Dynamic Adaptive Systems - A Runtime Testing Approach

Component-based software engineering has been continuously improved and successfully applied over the past years. Future systems, like ultra-large scale systems, are a vast array of decentralized, distributed, autonomic, heterogeneous, organically grown and continually evolving subsystems respectively components. Components may join or leave these systems during the life cycle of these systems, even at runtime. Despite this enormous complexity, we depend more and more on these dynamic adaptive systems. Hence we have to care about dependability although the systems are evolving at runtime. To achieve dependable dynamic adaptive systems which support hot plug and binding of components during runtime we claim to integrate specific concepts, like runtime testing, into the component infrastructure. In this paper we will show that existing approaches cannot guarantee the correctness of component bindings in dynamic adaptive systems. Therefore we introduce a technique for runtime testing and show how it can be integrated into a component-based approach.

IT ecosystems: A new paradigm for engineering complex adaptive software systems

Todays software-intensive systems are among the most complex artifacts created by men. This is due to ever increasing requirements and functionality of the software on the one hand, and to rising structural complexity with respect to size, interconnectedness, and distribution on the other hand. Engineering and controlling these systems pushes existing software engineering approaches to (and beyond) their limits [1]. This paper describes the concept of IT ecosystems as a new approach for addressing this challenge from the perspective of software engineering. The concept and approaches described were developed in a large interdisciplinary research project (www.it-oekosysteme.org); we present first results including a validation scenario of a smart airport, which has been devised and implemented in the project, aiming at a comprehensive approach to IT ecosystems engineering.

Indoor-Simulation of Team Training in Cycling

For the single cyclist performance parameters such as power, speed, or heart rate can be monitored during training and competition. Although cycling is primarily a single sport, riding in groups is a very common in training. An ambient intelligence system has been developed for the training of a group of cyclists. The objective of this system is to improve team training such that each cyclist is as close to his individual exercise intensity as possible. Besides physiological and biomechanical data, subjective sensations are also considered. The focus of this paper is on feedback training. Based on the comparison of dynamically collected status data and set values, the feedback training system adjusts training parameters, for instance by advising the group to change the order or the formation, to increase or decrease the speed, or to split the group. In a final version, the system should run under outdoor conditions. As an intermediate step, a prototype for indoor training was established.

Guaranteeing correctness of component bindings in dynamic adaptive systems based on runtime testing

Component-based software engineering has been continuously improved and successfully applied over the past years. Future systems, like ultra-large scale systems, are a vast array of decentralized, distributed, autonomic, heterogeneous, organically grown and continually evolving subsystems resp. components. Components join or leave these systems during the whole system life-cycle -- even during runtime. Since we depend on these dynamic adaptive systems we have to guarantee their correctness although they evolve during runtime. To guarantee system correctness and to support binding of components during runtime we claim to integrate specific concepts into a component infrastructure. In this paper we will introduce a technique for runtime testing.

Integrating Sensor Nodes into a Middleware for Ambient Intelligence

The development of infrastructures enabling dynamic and automated composition of IT systems is a big challenge. This paper addresses a new idea of allowing component-based systems to reconfigure themselves. Therefore, the authors propose DAiSI - a Dynamic Adaptive System Infrastructure for dynamic integration of components as well as their reconfiguration during runtime. Thereby, one of the features of the infrastructure is that it is capable of binding components based on their availability. In this paper the authors concentrate on presenting how resource constrained sensor nodes can be integrated into a system using this infrastructure.

Towards a Component Model supporting Proactive Configuration of Service-Oriented Systems

Components within service-oriented systems require a mechanism to get in touch with offered services. A traditional approach from the field of Web services is a discovery agency provided by the infrastructure, where service providers register and service requestors submit their queries. In the field of dynamic adaptive systems we deal with systems which change their behavior according to the needs of their users during runtime based on context information. Therefore, the wiring of service providers and service requestors - known as the system configuration - may change often. As a consequence of the dynamics it is reasonable not to let the service requestor take care about the service discovery. Instead we propose a component model enabling the proactive configuration of service-oriented systems which will be described in this paper.

From Software Systems to Complex Software Ecosystems: Model- and Constraint-Based Engineering of Ecosystems

Software is not self-supporting. It is executed by hardware and interacts with its environment. So-called software systems are complicated hierarchical systems. They are carefully engineered by competent engineers. In contrast, complex systems, like biological ecosystems, railway systems and the Internet itself, have never been developed and tested as a whole by a team of engineers. Nevertheless, those complex systems have the ability to evolve without explicit control by anyone, and they are more robust to dealing with problems at the level of their constituent elements than classical engineered systems. Consequently, in this article we introduce the concept of complex software ecosystems comprised of interacting adaptive software systems and human beings. Ecosystems achieve the demanded flexibility and dependability by means of a kind of higher-level regulatory system. Their equilibrium is continuously preserved through the appropriate balance between the self-adaptation and the self-control capabilities of an ecosystem’s participants.