SLA Establishment Decisions: Minimizing the Risk of SLA Violations

This thesis presents an approach for service providers to select an SLA portfolio that minimizes the SLA violation risk. It considers constraints on expected profit and available resources. The problem is addressed by applying decision theory and risk measures, especially by adapting the concept of portfolio selection by Harry Markowitz and the semi-variance. In order to capture a decision maker\u27s attitude towards risk, utility theory and the concept of risk aversion are used

Cloud Computing – A Classification, Business Models and Research Directions

Lately, a new computing paradigm has emerged: “Cloud Computing”. It seems to be promoted as heavily as the “Grid” was a few years ago, causing broad discussions on the differences between Grid and Cloud Computing. The first contribution of this paper is thus a detailed discussion about the different characteristics of Grid Computing and Cloud Computing. This technical classification allows for a well-founded discussion of the business opportunities of the Cloud Computing paradigm. To this end, this paper first presents a business model framework for Clouds. It subsequently reviews and classifies current Cloud offerings in the light of this framework. Finally, this paper discusses challenges that have to be mastered in order to make the Cloud vision come true and points to promising areas for future research

RISK-AWARE SLA ESTABLISHMENT IN AGREEMENT NETWORKS – AN EVALUATION

The rise of Software as a Service (SaaS) platforms is driven by the current trend towards customeroriented, agile and scalable service provisioning. Customers’ demand for highly specialized services can mostly not be met by a single provider that offers a holistic solution but by a consortium of providers that cooperate. In order to enable the combination of services and hence, the collaboration between different service providers, technical challenges like the compatibility of interfaces have to be dealt with. In addition, economic issues concerning profit, reliability and risk of service failure have to be taken into consideration. A model of Agreement Networks (ANs) is presented that illustrate the legal bindings that are established or under negotiation between service providers and a methodology is introduced that supports providers in ANs to decide on the establishment of a combination of Service Level Agreements (SLAs) that incurs the lowest risk of SLA violation. Finally, a benchmark for risk-based decisions is derived that serves to evaluate the efficiency of the choice. The impact of the available amount of monitoring data on the decision is investigated and a minimal amount of 100 observations for each SLA combination is suggested

Charging Point Usage in Germany—Automated Retrieval, Analysis, and Usage Types Explained

This study presents an approach to collect and classify usage data of public charging infrastructure in order to predict usage based on socio-demographic data within a city. The approach comprises data acquisition and a two-step machine learning approach, classifying and predicting usage behavior. Data is acquired by gathering information on charging points from publicly available sources. The first machine learning step identifies four relevant usage patterns from the gathered data using an agglomerative clustering approach. The second step utilizes a Random Forest Classification to predict usage patterns from socio-demographic factors in a spatial context. This approach allows to predict usage behavior at locations for potential new charging points. Applying the presented approach to Munich, a large city in Germany, results confirm the adaptability in complex urban environments. Visualizing the spatial distribution of the predicted usage patterns shows the prevalence of different patterns throughout the city. The presented approach helps municipalities and charging infrastructure operators to identify areas with certain usage patterns and, hence different technical requirements, to optimize the charging infrastructure in order to help meeting the increasing demand of electric mobility