Abstract
Due to the multi-hop, long-distance, and wireless backbone connectivity,
provisioning critical and diverse services face challenges such as low
latency and reliability. This paper proposes ioFog, an offline fog
architecture for achieving reliability and low latency in a large
backbone network. Our solution uses a Markov chain-based task prediction
model to offer dynamic service requirements with minimal dependency on
the Internet. The proposed architecture considers a central Fog
Controller (FC) to (i) provide a global status overview and (ii) predict
upcoming tasks of Fog Nodes for intelligent offloading decisions. The FC
also has the current status of the existing fog nodes in terms of their
processing and storage capabilities. Accordingly, it can schedule the
possible future offline computations and task allocations. ioFog
considers the requirements of individual IoT applications and enables
improved fog computing decisions. As compared to the existing offline
IoT solutions, ioFog improves service time significantly and service
delivery ratio up to 23%.