Layered fault management scheme for end-to-end transmission in internet of things

Internet of things (IoT) network makes the interaction between people and things more active and provides the connection among different existing networks. To ensure the reliability of end-to-end transmission through the hierarchical networks, fault management is of great importance. Current relative fault detection algorithms are designed for specified network, not suited to this complex communication environment. In this paper, we propose a layered fault management scheme for IoT with uniform observing points setting around. In order to distinguish between the real fault and false alarm, fuzzy cognitive maps theory is introduced to set up the monitoring model. By adjusting the weighting rules in the model, different observing points may realize flexible judgment of the link failure risk in their authorities. After locating the fault roots, original recovery method for individual networks may be used to rescue the broken transmission. The distributed working mode makes the proposed scheme more efficient and strong. This design may both realize quick fault discovery and use the existing implementation to the maximum extent. Simulation results show the effectiveness of the proposed scheme.