Mann, Zoltán ÁdámMetzger, AndreasPrade, JohannesSeidl, RobertFelderer, MichaelHasselbring, WilhelmRabiser, RickJung, Reiner2020-02-032020-02-032020978-3-88579-694-7https://dl.gi.de/handle/20.500.12116/31713Fog computing uses geographically distributed fog nodes that can supply nearby end devices with low-latency access to cloud-like compute resources. If the load of a fog node exceeds its capacity, some non-latency-critical application components may be offloaded to the cloud. Using commercial cloud offerings for such offloading incurs financial costs. Optimally deciding which application components to keep in the fog node and which ones to offload to the cloud is a difficult combinatorial problem. We introduce an optimization algorithm that (i) guarantees that the deployment always satisfies capacity constraints and affinity requirements, (ii) achieves near-optimal cloud usage costs, and (iii) is fast enough to be run online. The practical use of the algorithm is illustrated by applying it to optimizing the applications in a mobile factory.enFog ComputingCost-optimized Software DeploymentResource OptimizationText/Conference Paper10.18420/SE2020_351617-5468