An Inherent Fog Network: Brain-Spinal Cord-Nerve Networks

Abstract

The spinal cord plays a key role for big data processing in the central nervous system, which is composed of the brain and spinal cord. A close look to the spinal cord reveals that the main functions of fog nodes such as communication, computation, and storage capability define what spinal cord does in the central nervous system. Based on this analogy, a new network architecture is described dubbed brain-spinal cord-nerve network that bears a striking resemblance to cloud-fog-thing network architecture under consideration for 5G networks. A stochastic geometry analysis is performed for this network to specify the optimum number of special neurons at the spinal cord responsible for learning. Additionally, to provide an alternative model for some fundamental motor skills in our daily life such as driving, swimming, dancing, and the brain-spinal cord-nerve network is modeled as a coded cache. These findings can be quite useful for neuroscientists who may want to apply the fog network model to the central nervous system with the ultimate aim of treating serious central nervous system diseases. Lastly, a novel coded caching structure is developed for fog networks inspired by the central nervous system.

Keywords

• Fog networking
• spinal cord
• brain
• stochastic geometry
• caching