Towards Scalable Optimization of Large-Scale IoT Access for Mobile Users with Diverse Requirements

Fog computing is an emerging architecture, which extends the Cloud computing paradigm to the edge of the network, enabling new applications and services, including Internet of Things (IoT). End users have certain computation tasks, which can be completed either locally on the end device or remotely on an accessible Fog node via computation offloading. The access is wireless with severe physical limitations on the access network capacity to sustain stringent latency requirements for streaming and real-time applications. Robust access can be provided by maintaining connectivity to several Fog nodes. We propose a scalable access network management scheme, which intends to approximately maximizes the aggregate utility for large-scale networks comprised of a large number of Fog nodes and mobile users with vastly different bandwidth requirements and transmission power restrictions. Scalability is due to a two-level architecture, where each user only communicates with the "closest" Fog nodes, while different Fog nodes exchange aggregated information on the intercell interference. Future research should address accuracy and possible improvements to the approximations. We also plan to incorporate robustness constraints requiring connectivity to multiple Fog nodes.