Optimised fuzzy clustering-based resource scheduling and dynamic load balancing algorithm for fog computing environment

An influential and standard tool, fog computing performs applications of internet of things (IoT) and it is the cloud computing's extended version. In the network of edge computing, the applications of IoT are possibly implemented by fog computing which is an emerging technology. Load on cloud is minimised with proper resource allocation using fog computing methods. Throughput maximisation, available resources optimisation, response time reduction, and elimination of overloaded single resource are the goal of load balancing algorithm. This paper suggests an optimised fuzzy clustering-based resource scheduling and dynamic load balancing (OFCRS-DLB) procedure for resource scheduling and load balancing in fog computing. For resource scheduling, this paper recommends an enhanced form of fast fuzzy C-means (FFCM) with crow search optimisation (CSO) algorithm in fog computing. Finally, the load balancing is done using scalability decision technique. The proficiency of the recommended technique is obtained by comparing with other evolutionary methods.