Fog Computing as a Resource-Aware Enhancement for Vicinal Mobile Mesh Social Networking

Mobile Mesh Social Network (MMSN) represents an environment where the mobile device users are capable of performing various virtual social network activities such as sharing information, forming social groups, text messaging when they encounter each other in the physical vicinity within the wireless network range. Moreover, the characteristics of MMSN such as the Internetless activities and Wireless Mesh Network (WMN)-based connectivity provides various potentials including but not limited to business opportunities, scalable crowdsourcing or crowdsensing deployment, edge computing and so on. Although there exist a fair number of software platforms that help developers to implement MMSN, they still cannot fully overcome the limitation derived from the hardware resource constraint nature of the participative mobile devices. In order to enhance the MMSN in terms of cost efficiency, we introduce Fog Social Network (FSN) model, which utilises the computing and networking resources in users' close vicinity to improve the overall efficiency of MMSN. Further, the proposed FSN framework consists of an adaptive resource-aware cost-performance index (CPI) scheme, which performs dynamic approach selection autonomously at runtime to choose the most efficient route for the delivery of the messages for MMSN activities. With this intention, we have implemented and validated a proof-of-concept prototype.