Application Placement with Constraint Relaxation
By: Damiano Azzolini , Marco Duca , Stefano Forti and more
Potential Business Impact:
Places computer tasks smartly on many machines.
Novel utility computing paradigms rely upon the deployment of multi-service applications to pervasive and highly distributed cloud-edge infrastructure resources. Deciding onto which computational nodes to place services in cloud-edge networks, as per their functional and non-functional constraints, can be formulated as a combinatorial optimisation problem. Most existing solutions in this space are not able to deal with \emph{unsatisfiable} problem instances, nor preferences, i.e. requirements that DevOps may agree to relax to obtain a solution. In this article, we exploit Answer Set Programming optimisation capabilities to tackle this problem. Experimental results in simulated settings show that our approach is effective on lifelike networks and applications.
Similar Papers
Neuro-Symbolic Constrained Optimization for Cloud Application Deployment via Graph Neural Networks and Satisfiability Modulo Theory
Logic in Computer Science
Helps cloud computers place apps faster and cheaper.
Strategic Server Deployment under Uncertainty in Mobile Edge Computing
Distributed, Parallel, and Cluster Computing
Places computers smartly for faster phone use.
Optimal Multi-Constrained Workflow Scheduling for Cyber-Physical Systems in the Edge-Cloud Continuum
Networking and Internet Architecture
Makes smart devices work faster together.