Semantic Multimedia Fog Computing and Lot Environment: Slistainabilfly Perspective

We propose a fog-cloud hybrid architecture that can support a massive ad hoc crowd corn posed of a massive social network and distributed loT nodes around a smart city environment. The tog computing framework is introduced to support energy efficiency by incorporating loT nodes that act as an interface to the ad hoc crowd, is aware of user contexts within its vicinity, can do real-time processing of user requests, supports a constrained amount of data offloading, and pass the geo-tagged multimedia data available from the subset of the ad hoc crowd to the big data repository in the cloud. The framework leverages a sustainable crowdsourcing incentive model for both the ad hoc crowd and the loT infrastructure provider. The proposed sustainable framework can potentially support context-aware smart city services such as finding a lost person within the crowd, showing green and health risk prone zones, semantic and location-aware notifications of events of interest, semantic loT-based routing, and dealing with emergency situations. We present a communication architecture between mobile users and fog nodes, and between fog nodes and the cloud, a sustainability and energy efficiency model, and massive geo-tagged, multimedia big data architecture.