Towards Bandwidth Optimization in Fog Computing using FACE Framework

The continuous growth of data created by Internet-connected devices has been posing a challenge for mobile operators. The increase in the network traffic has exceeded the network capacity to efficiently provide services, specially for applications that require low latency. Edge computing is a concept that allows lowering the network traffic by using cloud-computing resources closer to the devices that either consume or generate data. Based on this concept, we designed an architecture that offers a mechanism to reduce bandwidth consumption. The proposed solution is capable of intercepting the data, redirecting it to a processing node that is allocated between the end device and the server, in order to apply features that reduce the amount of data on the network. The architecture has been validated through a prototype using video surveillance. This area of application was selected due to the high bandwidth requirement to transfer video data. Results show that in the best scenario is possible to obtain about 97% of bandwidth gain, which can improve the quality of services by offering better