The objective of this thrust of work is to develop models and tools for providing predictability for edge computing systems in the context of an infrastructure.
A key aspect of system wide predictability is the interaction between the network core and the edge systems, for instance with respect to orchestration and network slicing.
Further challenges arise from automating resource reservation and task allocation in large edge infrastructures, for instance with respect to load balancing, life-cycle management, detection and mitigation of latency/reliability anomalies while preserving the predictability properties for the running applications. The work in this subproject leverages methodologies from systems theory, optimization theory, as well as game theory.
Areas within Predictability:
Contacts
Focus area manager
György Dán
Edge computing, Resource management
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Focus area co-manager
Lei Feng
Mechatronics, Supervisory ctrl, Optimization, Model-checking
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Focus area co-manager
Rafia Inam
Trustworthy AI
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Focus area co-manager
James Gross
Wireless, Predictability, Edge computing
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