Priority-based fault tolerance mechanism with neighbour candidate node discovery algorithm and task processing by replication and forwarding technique under Fog-IoT wireless computing environments

The real-world exponential increase in data traffic has brought attention to a new computing paradigm termed Fog Computing (FC), which is intended for task offloading in fault-free fog networks. It is a potential aid which that provides greater processing aids at lower costs and with greater availability, flexibility, and cost. The issue typically arises due to the high task count and impacts task offloading in fog scenarios. In order to address a problem that arises in the Fog-IoT network for providing dependable and error-free transmission, an appropriate technique is required. Based on fault minimization and cost optimisation, the novel FT mechanism is proposed in this research. First, proposed Priority based Task offloading with Fault Tolerance (PToFT) scheme is used to identify the faulty-FNs using FN's remaining residual energy. To find the neighbour candidate Fog access node for replacing the faulty-FNs, the Min-cost Neighbour Candidate Node Discovery based on replication and forwarding (MNCND-RaF) technique is proposed for effective task processing and also tracks the task information towards the new nodes. These proposed methods are simulated, evaluated, and compared with the current Fault Tolerance (FT) techniques. The results shows that the compared results of the proposed methods will outperforms with current approaches like Without FT, NFT-WOA, and DFTLA methods, as 42.3 %, 36.2 %, and 27.7 %, respectively. Additionally, it utilized 1.53 J of residual energy as compared with HBI-LB and 0.84 J without replicas.