When deploying and running microservices (or closely related network function chains) to and in edge or core clouds, typical assumptions about these kinds of infrastructure prevail: it is dependable, does not fail, does not move. On that basis, many so-called orchestration algorithms have been designed; these algorithms decide, e.g., how many instances of a service to run, where each instance runs, and which instance serves which data flow.
This mindset, however, changes with new types of infrastructure: vehicles can be seen as a moving cloud, but only vehicles in the vicinity of a particular intersection can be of interest. Fleets of drones similarly can act as (very simple, very specialized) service providers; but they need to handover service execution once they run out of battery power and have to be replaced by another drone, for a few minutes. For such volatile, evolving infrastructures, there is very little in the literature about suitable orchestration concepts.
The goal of this thesis is hence to identify a suitable model for volatile infrastructure, to cast some typical orchestrations problems into that model and to design and to evaluate their performance. As this is a fairly open area, the topic is also fairly open and evolving the concept is clearly part of the thesis assignment.
- Familiar with cloud computing concepts and microservices / network function virtualization
- Ideally also familiar with vehicle-to-anything
- Good modeling skills
- Some experience in one of: optimization problems, heuristic design, machine learning is useful