Scientific Projects

These are the scientific research projects that I have been or am involve with:

Models to Increase the Cost Awareness of Cloud Developers


One of the challenges of modern cloud application development is the management of deployment costs. Automated and semi-automated scaling, pay-per-use pricing, complex multi-factor billing models, and frequent changes in the market make predicting the actual costs of using a given (combination of) cloud services to host a given application so that it exhibits a given level of minimal performance (e.g., response time) difficult for developers. The primary contribution  of MInCA will be an approach to model, predict and optimize the deployment costs of cloud applications, with a specific focus on (micro-)service-based applications. Central to our approach is the notion of a holistic cost model (HCM), which is a multi-view architectural model of the application that integrates modelling the dependencies between services, the deployment of the individual services onto cloud resources,and the application workload (e.g., what load is on what service at what times). We will use the HCM to foster developer awareness of the cost impact of their code changes (e.g., through appropriate visualizations in the Integrated Development Environment, IDE), to support What-If analysis (“What happens if the application gets 50% more users?”), and to enable application-wide deployment optimization (i.e., select optimal deployment options for each service depending on global state and available cloud services).

Funding Agency:  Swiss National Science Foundation (SNF)

Funded Amount: 182’963 CHF

Role: Applicant and Principle Investigator

Time Frame: September 2016 – August 2019

Towards Software Developer Targeted Cloud Benchmarking and Cost Estimation


In cloud-based software development, applications are deployed to virtual machines using a predefined cloud instance type. These types differ in provided performance as well as costs. Software developers currently struggle with selecting the best (i.e., cost-optimal) instance types to deploy their applications. In DevCloud, we provide methods and tooling that enable cloud benchmarking for software developers. Our approach is based on application-specific performance models, which combine a statistical model of cloud instance performance as delivered by cloud benchmarking research, an architectural application model, and example load and usage patterns.

Funding Agency:  Hasler Foundation

Funded Amount: 44’791 CHF

Role: Co-Applicant, Co-PI

Time Frame: Jan 2016 – Sept 2016

Agile Service Engineering for the Future Internet


CloudWave researches agile development and delivery of adaptive cloud services, which dynamically adjust to changes in their environment so as to optimise service quality and resource utilization. CloudWave will deliver (1) an open architecture and standards-based reference implementation of an advanced cloud software stack, with novel capabilities for adaptation across all cloud layers; and (2) tools and methods for agile development of reliable and adaptable cloud services, facilitated by the new stack. Our main interest in CloudWave lies in the idea of Feedback-Driven Development for cloud applications: an cloud-based software development approach, where developers exploit runtime analytics data to incrementally determine and evolve application features, extensions and optimizations, based on observed user needs.

Funding Agency:  The European Union’s 7th Framework Programme, Call 10

Role: Researcher, Co-Principle Investigator for University of Zurich

Time Frame: Nov 2013 – Oct 2016

Autonomous Control for a Reliable Internet of Services


Currently, we are witnessing a paradigm shift from the traditional information-oriented Internet into an Internet of Services (IoS). This transition opens up virtually unbounded possibilities for creating and deploying new services. Eventually, the ICT landscape will migrate into a global system where new services are essentially large-scale service chains, combining and integrating the functionality of (possibly huge) numbers of other services offered by third parties, including cloud services. Motivated by this, the aim of ACROSS is to create a European network of experts, from both academia and industry, aiming at the development of autonomous control methods and algorithms for a reliable and quality-aware IoS.

Funding Agency: European Cooperation in Science and Technology (COST)

Role: Working Group Leader and Substitute Management Committee Member for Switzerland

Time Frame: October 2014 – October 2016

Augmented Diagnosis and Testing for SOAs

(Audit 4 SOAs)

Audit 4 SOAs addresses one of the current major problems in Service-oriented Architectures (SOAs) development: testing support. In particular, the project is focused on a systematic testing and diagnosis approach of complex SOAs with the help of real world quality environments.

Funding Agency: FWF – der Wissenschaftsfonds

Role: Researcher

Time Frame: May 2011 – April 2014


Indenica aims at a major contribution to the Future Internet by providing Virtual Service Platforms as a novel domain-specific approach to create service-based applications. In particular, this approach will ease the development of domain-specific, service-based applications by resolving the quality, interface, and technology fragmentation that can be observed in todays service platforms.

Funding Agency: 7th Framework Programme of the European Commission

Role: Consultant

Time Frame: October 2010 – September 2013


S-Cube, the European Network of Excellence in Software Services and Systems, has established an integrated, multidisciplinary, vibrant research community, enabling Europe to lead the software-services revolution and helping shape the software-service based Internet which is the backbone of our future interactive society.

Funding Agency: 7th Framework Programme of the European Commission

Role: Researcher and Deputy Work Package Leader

Time Frame: March 2008 – February 2012

Celtic Madeira

The goal of the Madeira project was to provide novel technologies for a logically meshed Network Management System (NMS) that can handle dynamic behaviour of transient network elements. This should enable self-managed services to run on networks with increased numbers of network elements, greater heterogeneity and transience.

Funding Source: EUREKA

Role: Researcher

Time Frame: 2006 – 2007