PhD position on Performance Observability in Cloud-Edge Continuum (1.0 FTE)
- Hours per week:
- 38 to 40
- Faculty of Science
- Department of Information and Computing Sciences, Intelligent Software Systems
- Application deadline:
Nowadays large-scale software applications (e.g., streaming and gaming services, enterprise applications) are running on distributed systems that are evolving towards an interconnected continuum consisting of high-end cloud servers to mid-range fog gateways and low-end heterogeneous edge devices. On the one hand, such a scalable continuum continues to improve the agility, responsiveness and effectiveness of highly distributed applications. On the other hand, this paradigmatic shift has also introduced significant complexities to the resource and service management layers. These include challenges related to performance optimisation and maintenance in large-scale distributed systems. Of particular interest are the so-called performance variability and degradation issues, which often impact the reliability of the infrastructure and services. Simply put, variability and degradation refer to fluctuating application performance indicators due to anomalous performance events (e.g., resource interference, unpredictable workload, or correlated faults) in the underlying infrastructure, further inducing undesirable performance behaviour and service outages. Such issues will only aggravate due to cloud-edge systems' increasing scale and heterogeneity. This calls for the need to research cloud-edge management paradigms with more visibility and control over system parameters, infrastructure dependencies, and application constraints impacting the performance.
In this PhD position you focus on contributing to the theory and design of holistic performance observability (i.e. measuring the internal states of a system by examining its output) solutions in cloud-edge based systems. You will focus on diagnosis, prognosis, causal attribution and analysis of anomalous performance events, evaluating their impacts/trade-offs, localising their actual root cause (s), and suggesting or actuating mitigations. You contribute to our long-term objective to define open standards and develop observability benchmarks that enhances experiment reproducibility in cloud-edge systems.
- analyse the literature to understand the state-of-the-art in edge-cloud performance observability, diagnosis, prognosis and their limiting factors in resource management;
- design a generalised observability theory and understand the ramifications of design choices, restrictions, and trade-offs in large scale cloud-edge systems;
- research and implement diagnosis and prognosis algorithms to infer the observable and non-observable anomalous events when localising their causality;
- develop a performance management prototype that benchmarks degradation and variability scenarios in a controlled environment and validates them based on the developed observability theory and heuristics to provide early detection and mitigation of performance issues.
The position includes research as well as teaching. Approximately 30% of your time will be spent performing varying teaching (support) activities. We offer the opportunity to take significant steps towards acquiring a basic teaching qualification (BKO), which qualifies you as a teacher in the Dutch higher education system.
You have a critical mindset with an independent outlook in defining and solving research problems. With your collaboration and communication skills you are a valuable asset to our team. We would also like you to bring the following qualifications:
- a Master’s degree in Computer Science, Computational Science or related field;
- knowledge of or interest in the broader research area of distributed systems, cloud-edge computing, and multi-objective optimisation is a plus;
- demonstrated programming skills (e.g. Python, Java, Go) with experience in building system prototypes for demonstrating proof of concept;
- experience with DevOps technologies (e.g. Dockers, Kubernetes) is a plus;
- good academic writing with a strong command of English, both in speaking and writing.
We offer an exciting opportunity to collaborate with leading cloud, edge and distributed computing researchers, present your work at leading international conferences and conduct research abroad. You get the chance to follow personal and professional training courses in the Graduate School of Natural Sciences of Utrecht University.
Besides this, we offer:
- a full-time position for five years;
- a full-time gross salary that starts at €2,541 and increases to €3,247 per month (scale P of the Collective Labour Agreement Dutch Universities (CAO));
- 8% holiday bonus and 8.3% end-of-year bonus;
- a pension scheme, partially paid parental leave, and flexible employment conditions based on the Collective Labour Agreement Dutch Universities.
In addition to the employment conditions laid down in the CAO for Dutch Universities, Utrecht University has a number of its own arrangements. For example, there are agreements on professional development, leave arrangements and sports. We also give you the opportunity to expand your terms of employment via the Employment Conditions Selection Model. This is how we like to encourage you to continue to grow.
More information about working at the Faculty of Science can be found here.
About the organisation
The PhD position is embedded in the division Intelligent Software Systems within the research group of Organisation and Information. This group is part of the Department of Information and Computing Sciences.The department is nationally and internationally renowned for its fundamental and applied research in computer science and information science. In our constantly changing (digital) society, the Department of Information and Computing Sciences is constantly looking for new, realistic ways to push the boundaries of both science and social application. We contribute to innovative information technologies through the development and application of new concepts, theories, algorithms, and software methods. Relevant areas of interdisciplinary research include Game Research, Foundations of Complex Systems, Applied Data Science, and Artificial Intelligence.
At the Faculty of Science, there are 6 departments to make a fundamental connection with: Biology, Chemistry, Information and Computing Sciences, Mathematics, Pharmaceutical Sciences, and Physics. Each of these is made up of distinct institutes that work together to focus on answering some of humanity’s most pressing problems. More fundamental still are the individual research groups – the building blocks of our ambitious scientific projects. Find out more about us.
Utrecht University is a friendly and ambitious university at the heart of an ancient city. We love to welcome new scientists to our city – a thriving cultural hub that is consistently rated as one of the world’s happiest cities. We are renowned for our innovative interdisciplinary research and our emphasis on inspirational research and excellent education. We are equally well-known for our informal atmosphere and the can-do mentality of our people. This lively and inspiring academic environment attracts professors, researchers and PhD candidates from all over the globe, making both the University and the Faculty of Science a vibrant international and wonderfully diverse community.
Everyone deserves to feel at home at our university. We welcome employees with a wide variety of backgrounds and perspectives. If you have the expertise and the experience to excel in this role, then simply respond via the “Apply now” button!
- a letter of motivation;
- your curriculum vitae, including a list of accepted or submitted publications (if any);
- copy of your MSc diploma and transcripts or a letter from your MSc thesis supervisor indicating when you are likely to graduate;
- copy of your MSc Thesis;
- names, telephone numbers, and email addresses of at least two references.
If this specific opportunity isn’t for you, but you know someone else who may be interested, please forward this vacancy to them.
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The application deadline is 7 July 2022.