Abstract
•“Internet of Things based Smart City Design using Fog Computing and Fuzzy Logic”.•An edge computing paradigm using human interactions for their decision-making process.•Employs probabilistic history-based parameters that keep track of node interactions.•Context-aware smart paradigm considering predictability ratios.•A nature-inspired algorithm used to make the routing considerations.•A fuzzy rule-based system using power-buffer capacity-based index to make classes.
The prevalence of IoT based technology in contemporary society allows for the planning of smart city infrastructure with individually owned devices as participating nodes in a social smart network. Edge computing application into such an IoT network facilitates the distributed computing framework by bringing the computational application closer to the end-users in form of Fog sub-networks, comprising the local participating end-user IoT nodes as service requesters and specialized servers catering to the requests, modelled for the infrastructure category they are delivering (Smart healthcare, ITS, Smart architecture, etc.). Opportunistic-based last-mile connectivity between the Fog servers and participating nodes aides the dynamicity of the topology for efficient information. Aiding the same, the proposed edge computing enabled, sustainable, opportunistic IoT-based intuitive data exchange, collection and operation scheme that employs a dynamic routing procedure that considers human interactions, their movement patterns and their decision-making process. The proposed scheme employs probabilistic history-based parameters that keep track of node interactions. The interactions are modelled on the Firefly PSO, allowing exploitation of the social mobility. The Fuzzy logic is used for hop decision making based on the social and attribute-based parameters which mimic intuitive and pragmatic decision making of humans in terms of social interactions and mobility.