IOT BASED MEMORY FAULT DIAGNOSIS AND REPAIRING USING PARTICLE SWARM OPTIMIZATION (PSO)

Abstract

With the advent of Internet of Things based devices, there has been an increased focus on memory, which is an integral part of IoT. As the requirement of memory increased, the probability of fault occurrence will also increase. Research problem addresses the requirement of efficient and autonomous system for detecting and repairing faults in IoT devices using BPSO. As IoT devices are widespread in many applications, ensuring the reliability becomes of foremost relevance. If any of these faults is undetected, then it leads to significant system failures. Traditional methods may not provide the necessary scalability, adaptability and efficiency for the IoT devices. This research aims to enhance the reliability of IoT devices by optimizing fault processes. The adoption of BPSO offers a novel approach to addressing the limitations of traditional fault detection methods, with the potential to significantly improve the performance and reliability of IoT networks. For Optimization, Binary particle Swarm Optimization algorithm is considered using certain parameters like storage temperature, Reference clock frequency, Power consumption, voltage level, ground loop, humidity, output current and EM Interference. On the basis of change in these parameters faults are generated. Once the faults are generated an optimization of fault is done with the help of BPSO in order to create an optimized fault dictionary. This fault dictionary provides the information which faulty memory location is to be repaired first. So that repair solution on the faulty memories can be applied. As in this article we have considered three faults individually stuck at Fault, Transition Fault and Coupling Fault for memory size 16x8x8 and 32x8x8 with spare memory 2*8*8 and 4*8*8. The result shows that the fault rate for optimization using fault detection method is 90.62% where as optimization using BPSO fault rate is 100%. This method provides better fault coverage for wide range of memory faults. However, it might require additional computation time.