Abstract
With the emerging Internet of Things (IoT), distributed systems enter a new era. While pervasive and ubiquitous computing already became reality with the use of the cloud, IoT networks present new challenges because the ever growing number of IoT devices increases the latency of transferring data to central cloud data centers. Edge and fog computing represent practical solutions to counter the huge communication needs between IoT devices and the cloud. Considering the complexity and heterogeneity of edge and fog computing, however, resource provisioning remains the Achilles heel of efficiency for IoT applications. According to the importance of operating-system virtualization (so-called containerization), we propose an application-aware container scheduler that helps to orchestrate dynamic heterogeneous resources of edge and fog architectures. By considering available computational capacity, the proximity of computational resources to data producers and consumers, and the dynamic system status, our proposed scheduling mechanism selects the most adequate host to achieve the minimum response time for a given IoT service. We show how a hybrid use of containers and serverless microservices improves the performance of running IoT applications in fog-edge clouds and lowers usage fees. Moreover, our approach outperforms the scheduling mechanisms of Docker Swarm.
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Acknowledgement
This research has been funded by the European Union’s Horizon 2020 Framework Programme for Research and Innovation under Grant Agreement No. 785907 (Human Brain Project SGA2).
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Fard, H.M., Prodan, R., Wolf, F. (2020). A Container-Driven Approach for Resource Provisioning in Edge-Fog Cloud. In: Brandic, I., Genez, T., Pietri, I., Sakellariou, R. (eds) Algorithmic Aspects of Cloud Computing. ALGOCLOUD 2019. Lecture Notes in Computer Science(), vol 12041. Springer, Cham. https://doi.org/10.1007/978-3-030-58628-7_5
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