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Fog and Edge Computing by Satish Narayana Srirama, Rajkumar Buyya

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7 A Lightweight Container Middleware for Edge Cloud Architectures

David von Leon Lorenzo Miori Julian Sanin Nabil El Ioini Sven Helmer and Claus Pahl

7.1 Introduction

In typical cloud applications, most of the data processing is done on the back end and the clients are relatively thin. Integrating Internet‐of‐Things (IoT) devices and sensors into such an environment in a straightforward manner causes several problems. If billions of new devices start shipping data into the cloud, this will have a major impact on the flow of network traffic. Also, certain applications require real‐time behavior (e.g. self‐driving cars) and cannot afford to wait for data, which may arrive late due to network delays. Finally, users may also not want to send sensitive or private data into the cloud, losing control over it (this is especially important for healthcare applications). Consequently, cloud computing is moving away from large, centralized structures toward multicloud environments. The integration of cloud and sensor‐based IoT environments results in edge cloud or fog computing [1, 2], in which a substantial part of the data processing takes place on the IoT devices themselves. Rather than moving data from the IoT to the cloud, the computation moves to the edge of the cloud [3].

However, when running these kinds of workloads on such an infrastructure, we are confronted with different issues: the deployed devices are constrained in terms of computational power, storage capability, ...

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