Fog computing through public-resource computing and storage

Fog computing is a model in which data and processing are concentrated on devices at the edge of the network, rather than almost entirely in the cloud. This new paradigm tries to solve the latency and bandwidth issues that the current cloud systems have to deal with, and also addresses the scalability problems caused by the exponential growth of the number of smart devices due to the success of the Internet of Things. In this paper we introduce the idea of using public-resource computing and storage techniques in order to process part of the workload of the current cloud systems so as to avoid saturating the cloud. This idea proposes the use of devices working as participants, which form a data center between the cloud service providers and the end-clients. A participant can be any type of device, from a traditional PC (Personal Computer), to a smartphone or tablet or even a smart TV. We have evaluated two different case studies by simulating the use of participating nodes in video-transfer applications. The results of the simulations demonstrate that public-resource computing and storage can be used to solve the latency and bandwidth issues that affect the current cloud systems. Therefore, our results represent a feasible solution for applications that process or store public data.