Delivering cloud-like computing facilities at the network edge provides computing services with ultra-low-latency access, yielding highly responsive computing services to application requests. The concept of fog computing has emerged as a computing paradigm that adds layers of computing nodes between the edge and the cloud, also known as <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">micro data centers</i> , <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">cloudlets</i> , or <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">fog nodes</i> . Based on this premise, this article proposes a component-based service scheduler in a cloud-fog computing infrastructure comprising several layers of fog nodes between the edge and the cloud. The proposed scheduler aims to satisfy the application’s latency requirements by deciding which services components should be moved upwards in the fog-cloud hierarchy to alleviate computing workloads at the network edge. One communication-aware policy is introduced for resource allocation to enforce resource access prioritization among applications. We evaluate the proposal using the well-known iFogSim simulator. Results suggest that the proposed component-based scheduling algorithm can reduce average delays for application services with stricter latency requirements while still reducing the total network usage when applications exchange data between the components. Results have shown that our policy was able to, on average, reduce the overload impact on the network usage by approximately 11 percent compared to the best allocation policy in the literature while maintaining acceptable delays for latency-sensitive applications.
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