PREDICTING AVAILABILITY AND RESPONSE TIMES OF IT SERVICES

When IT service providers adapt their IT system landscapes because of new technologies or changing business requirements, the effects of changes to the quality of service must be considered to fulfill service level agreements. Analytical prediction models can support this process in the service design stages, but dependencies between quality aspects are not taken into account. In this paper, a novel approach for predicting availability and response time of an IT service is developed, which is simulation-based to support dynamic analysis of service quality. The correctness of the model as well as its applicability in a real case can be evaluated. Therefore, this work presents a step towards an analytical framework for predicting IT service quality aspects

Integrated Optimization of IT Service Performance and Availability Using Performability Prediction Models

Optimizing the performance and availability of an IT service in the design stage are typically considered as independent tasks. However, since both aspects are related to one another, these activities could be combined by applying performability models, in which both the performance and the availability of a service can be more accurately predicted. In this paper, a design optimization problem for IT services is defined and applied in two scenarios, one of which considers a mechanism in which redundant components can be used both for failover as well as handling overload situations. Results show that including such aspects affecting both availability and performance in prediction models can lead to more cost-effective service designs. Thus, performability prediction models are one opportunity to combine performance and availability management for IT services

Analysis of ICT services by observing “fit for use” attributes

As organisations depend more and more on ICT services to meet their missions, ICT disruptions constitute an important risk to their resilience. Therefore, a systematic approach to prevent, predict and manage ICT services disruptions along their life cycle is needed. Simulation and visualisation techniques have been suggested as a means to explore “what-if” scenarios that allow organisations to prepare for different outcomes and consequently help them to improve their resilience. The research discussed in this paper explores how visual analysis of simulated scenarios can be used as a decision support mechanism to evaluate ICT readiness for organisational resilience. In particular, it presents how this can be supported by our extension of xArchiMate, a tool for simulating and visualising enterprise architecture models. This approach is evaluated by conducting experiments using the tool, analysing the results, and discussing how other extensions can be made to model additional scenarios

An adaptive trust based service quality monitoring mechanism for cloud computing

Cloud computing is the newest paradigm in distributed computing that delivers computing resources over the Internet as services. Due to the attractiveness of cloud computing, the market is currently flooded with many service providers. This has necessitated the customers to identify the right one meeting their requirements in terms of service quality. The existing monitoring of service quality has been limited only to quantification in cloud computing. On the other hand, the continuous improvement and distribution of service quality scores have been implemented in other distributed computing paradigms but not specifically for cloud computing. This research investigates the methods and proposes mechanisms for quantifying and ranking the service quality of service providers. The solution proposed in this thesis consists of three mechanisms, namely service quality modeling mechanism, adaptive trust computing mechanism and trust distribution mechanism for cloud computing. The Design Research Methodology (DRM) has been modified by adding phases, means and methods, and probable outcomes. This modified DRM is used throughout this study. The mechanisms were developed and tested gradually until the expected outcome has been achieved. A comprehensive set of experiments were carried out in a simulated environment to validate their effectiveness. The evaluation has been carried out by comparing their performance against the combined trust model and QoS trust model for cloud computing along with the adapted fuzzy theory based trust computing mechanism and super-agent based trust distribution mechanism, which were developed for other distributed systems. The results show that the mechanisms are faster and more stable than the existing solutions in terms of reaching the final trust scores on all three parameters tested. The results presented in this thesis are significant in terms of making cloud computing acceptable to users in verifying the performance of the service providers before making the selection