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The advent of the Internet of Things (IoT) leads to the pervasion of business and private spaces with ubiquitous, networked computing devices. These devices do not simply act as sensors, but feature computational, storage, and networking resources. These resources are close to the edge of the network, and it is a promising approach to exploit them in order to execute IoT services. This concept is known as fog computing. Despite existing theoretical foundations, the adoption of fog computing is still at its very beginning. Especially, there is a lack of approaches for the leasing and releasing of resources. To resolve this shortcoming, we present a conceptual framework for fog resource provisioning. We formalize an optimization problem which is able to take into account existing resources in fog/IoT landscapes. The goal of this optimization problem is to provide delay-sensitive utilization of available fog-based computational resources. We evaluate the resource provisioning model to show the benefits of our contributions. Our results show a decrease in delays of up to 39% compared to a baseline approach, yielding shorter round-trip times and makespans.
Skarlat et al. (Tue,) studied this question.