Author: Andreas Dittrich Ph.D. Thesis, submitted to the Faculty of Mathematics and Natural Sciences, Humboldt University of Berlin, December 9, 2014. Oral defense March 20, 2015. Grade: magna cum laudae. Reviewers: Prof. Dr. Miroslaw Malek, Lugano, Switzerland Prof. Dr. Alexander Reinefeld, Berlin, Germany Prof. Dr. Jörg Kaiser, Magdeburg, Germany Download: published version, meta information

Dependability of service provision is one of the primary goals in modern networks. Since providers and clients are part of a connecting Information and Communications Technology (ICT) infrastructure, service dependability varies with the position of actors as the ICT devices needed for service provision change. We present two approaches to quantify user-perceived service dependability. The first is a model-driven approach to calculate instantaneous service availability. Using input models of the service, the infrastructure and a mapping between the two to describe actors of service communication, availability models are automatically created by a series of model to model transformations. The feasibility of the approach is demonstrated using exemplary services in the network of University of Lugano, Switzerland. The second approach aims at the responsiveness of the service discovery layer, the probability to find service instances within a deadline even in the presence of faults, and is the main part of this thesis. We present a hierarchy of stochastic models to calculate user-perceived responsiveness based on monitoring data from the routing layer. Extensive series of experiments have been run on the Distributed Embedded Systems (DES) wireless testbed at Freie Universität Berlin. They serve both to demonstrate the shortcomings of current discovery protocols in modern dynamic networks and to validate the presented stochastic models. Both approaches demonstrate that the dependability of service provision indeed differs considerably depending on the position of service clients and providers, even in highly reliable wired networks. The two approaches enable optimization of service networks with respect to known or predicted usage patterns. Furthermore, they anticipate novel service dependability models which combine service discovery, timeliness, placement and usage, areas that until now have been treated to a large extent separately.

	Authors: Andreas Dittrich Björn Lichtblau Rafael Rezende Miroslaw Malek 17th International GI/ITG Conference on “Measurement, Modelling and Evaluation of Computing Systems” and “Dependability and Fault-Tolerance”, MMB & DFT 2014, Bamberg, Germany, March 17-19, 2014 Download: accepted version, the final publication is available at link.springer.com

In service networks, discovery plays a crucial role as a layer where providers can be published and enumerated. This work focuses on the responsiveness of the discovery layer, the probability to operate successfully within a deadline, even in the presence of faults. It proposes a hierarchy of stochastic models for decentralized discovery and uses it to describe the discovery of a single service using three popular protocols. A methodology to use the model hierarchy in wireless mesh networks is introduced. Given a pair requester and provider, a discovery protocol and a deadline, it generates specific model instances and calculates responsiveness. Furthermore, this paper introduces a new metric, the expected responsiveness distance der, to estimate the maximum distance from a provider where requesters can still discover it with a required responsiveness. Using monitoring data from the DES testbed at Freie Universität Berlin, it is shown how responsiveness and der of the protocols change depending on the position of nodes and the link qualities in the network.

	Authors: Rafael Rezende Andreas Dittrich Miroslaw Malek 19th IEEE Pacific Rim International Symposium on Dependable Computing (PRDC), Vancouver, BC, Canada, December 2-4, 2013 Download: accepted version, final published version

Today’s businesses rely ever more on dependable service provision deployed on information and communications technology (ICT) infrastructures. Service dependability is highly influenced by the individual infrastructure component properties. Combining these properties for consistent dependability analysis is challenging as every service requester might use a different set of components during service usage, constituting the user-perceived view on a service. This paper presents a methodology to evaluate user-perceived instantaneous service availability. It uses three input models: (1) The ICT infrastructure, with failure rates, repair rates and deployment times of all components, (2) an abstract description of complex hierarchical services, (3) a mapping that contains concrete ICT components for the service pair requester and provider, as well as their existing replicas, and a duration of usage. The methodology then automatically generates an availability model from those parts of the ICT infrastructure needed during provision for the specified pair. To calculate instantaneous availability, the age of the ICT components, the order and time of their usage during service provision are taken into account. The methodology supports generation of different availability models, we demonstrate this by providing reliability block diagrams and fault-trees. We demonstrate the feasibility of the methodology by applying it to parts of the network infrastructure of University of Lugano, Switzerland.

	Authors: Andreas Dittrich Rafael Rezende 14th European Workshop on Dependable Computing (EWDC), Coimbra, Portugal, May 15-16, 2013 Download: accepted version, the final publication is available at link.springer.com

Service-oriented architecture (SOA) has emerged as an approach to master growing system complexity by proposing services as basic building elements of system design. However, it remains difficult to evaluate dependability of such distributed and heterogeneous functionality as it depends highly on the properties of the enabling information and communications technology (ICT) infrastructure. Moreover, every specific pair service client and provider can utilize different ICT components, constituting for the user-perceived view of a service. We provide a model-driven methodology to automatically create reliability block diagrams of such views. Given a service description, a network topology model and a pair service client and provider, it identifies relevant ICT components and generates a user-perceived service availability model (UPSAM). We then use this UPSAM to calculate the steady-state availability of different views on an exemplary mail service deployed in the network infrastructure of University of Lugano, Switzerland.

	Authors: Andreas Dittrich Igor Kaitovic Cristina Murillo Rafael Rezende 27th IEEE International Symposium on Parallel Distributed Processing, Workshops and PhD Forum, IPDPSW 2013, Boston, MA, USA, May 20-24, 2013 Download: accepted version, final published version

An ever-increasing number of both functional and non-functional requirements has resulted in growing system complexity which demands new solutions in system modeling and evaluation. As a remedy, service-oriented architecture (SOA) offers services as basic building elements of system design. Service dependability is highly dependent on the properties of the underlying information and communications technology (ICT) infrastructure. This is especially true for the user-perceived dependability of a specific pair service client and provider as every pair may utilize different ICT components. We provide a model for the description of ICT components and their non-functional properties based on the Unified Modeling Language (UML). Given a service description, a network topology model and a pair service client and provider, we propose a methodology to automatically identify relevant ICT components and generate a user-perceived service infrastructure model (UPSIM). We demonstrate the feasibility of the methodology by applying it to parts of the service network infrastructure at University of Lugano (USI), Switzerland. We then show how this methodology can be used to facilitate user-perceived service dependability analysis.