A vast and growing number of IoT applications connect physical devices, suchas scientific instruments, technical equipment, machines, and cameras, across heterogeneous infrastructure from the edge to the cloud . As edge and cloud layers are increasingly tightly integrated, imbalancedresource allocations and sub-optimally placed tasks can quickly deteriorate the overall system performance . This paper proposes an emulation approach for the investigation of task placements across the edge-to-cloud continuum . The right task placement strategy has a significant impact on performance — in our experiments, between 5% and65% depending on the scenario, according to the paper . We evaluate our approach using a machinelearning-based workload, demonstrating the validity by comparing emulation andreal-world experiments. Further, we show that the righttask placement strategyhas a significant effect on performance . Further, the right task placement strategy has an impact on the right Task Placency is up to 5% to

Author(s) : Andre Luckow, Kartik Rattan, Shantenu Jha

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Keywords : task - placement - cloud - edge - performance -

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