Improving the reliability in bio-nanosensor modules using hardware redundancy techniques

Abstract

A nano-robot is a controlled robotic system at the nanoscale. Nowadays, nanorobotics has become of particular interest in medicine and pharmacy. The accurate diagnosis of the diseases as well as their rapid treatment will make everyone surprised and will significantly reduce the associated risks. The modeling of reliability in biosensors is studied for the first time in this paper. The use of practical hardware redundancy has turned into the most cost-effective to improve the reliability of a system. Additionally, the Markov model is used to design fault-tolerant systems in nanotechnology. The proposed method is compared with some existing methods, such as triple modular redundancy and non-fault-tolerant systems; it is shown that using this method, a larger number of faults between 3-5 can be tolerated. Using the proposed method, the number of modules can be increased to nine. However, a larger number than 9 MR is not recommended because of an increased delay and requiring more hardware. As the scale of components used in digital systems has gotten smaller, the use of hardware redundancy has become cost-effective. But there is a trade-off between the amount of used hardware and fault tolerance, which can also be investigated.