Cosmin Florin Avasalcai
Quality of Service aware Resource Provisioning in Edge Computing
- Main supervisor: Prof. Schahram Dustdar, firstname.lastname@example.org (contact person)
- Co-supervisor: N.N -> formerly Assistant Prof. Stefan Schulte, email@example.com
- Enable resource provisioning for large-scale Fog environments, considering their volatility.
- Develop resource provisioning and management techniques for resource allocation under given Quality of Service (QoS) constraints targeting non-critical applications, ensuring non-interference with critical apps.
- Models for Fog resources, and definition of optimization problems and metrics for resource provisioning.
- Development of prototype provisioning mechanisms for self-adaptation, supporting the fusion and dissolution of groups of Fog Nodes, data/state migration, sharing, replication, as well as the resource allocation services.
- Development of mechanisms for self-optimizing resource allocation and task scheduling.
- Evaluate the devised approaches, via simulations and real-world experiments.
- Develop services that enable pricing plans used in cost-to-serve infrastructure use.
Planned Visits and Collaboration:
- MDH (Assoc. Prof. Moris Behnam): Define the API for the resource management jointly with MDH and ABB
- DTU (Prof. Paul Pop): Define a resource management framework to efficiently host IoT applications at the edge of the network.
Within this PhD project, the candidate is expected to develop optimization approaches for resource allocation and task scheduling in the fog. For this, the candidate is expected to apply techniques from the fields of Machine Learning and/or (Linear) Optimization. The work conducted within this project will follow an iterative approach, starting with centralized, optimal solutions but later on working on decentralized, optimal and heuristic approaches.
For a complete list of publications please visit the following page: Publication Page
- Nardelli M., Nastic S., Dustdar S., Villari M., Ranjan R. (2017). Osmotic Flow: Osmotic Computing+ IoT Workflow. IEEE Cloud Computing, Volume 4, Issue 2, pp. 68-75
- Villari M., Fazio M., Dustdar S., Rana O., Ranjan R. (2016). Osmotic Computing: A New Paradigm for Edge/Cloud Integration. IEEE Cloud Computing, Volume 3, Issue 6, pp. 76-83