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Meeting the requirements of future services with time sensitivity andhandling sudden load spikes of the services in Fog computing environments arechallenging tasks due to the lack of publicly available Fog nodes and theircharacteristics. Researchers have assumed that the traditional autoscalingtechniques, with lightweight virtualisation technology (containers), can beused to provide autoscaling features in Fog computing environments, fewresearchers have built the platform by exploiting the default autoscalingtechniques of the containerisation orchestration tools or systems. However, theadoption of these techniques alone, in a publicly available Fog infrastructure,does not guarantee Quality of Service (QoS) due to the heterogeneity of Fogdevices and their characteristics, such as frequent resource changes and highmobility. To tackle this challenge, in this work we developed a Fog as aService (FaaS) framework that can create, configure and manage the containerswhich are running on the Fog devices to deploy services. This work presents thekey techniques and algorithms which are responsible for handling sudden loadspikes of the services to meet the QoS of the application. This work providesan evaluation by comparing it with existing techniques under real scenarios.The experiment results show that our proposed approach maximises the satisfiedservice requests by an average of 1.9 times in different scenarios.

Fog Device-as-a-Service (FDaaS): A Framework for Service Deployment in Public Fog Environments