Optimal sensor spacing in IoT network based on quantum computing technology

Abstract

Quantum computing has gained an advantage in recent years due to its compatibility and usage in various fields. The IoT environment is huge, and almost the whole world relies on it to acquire efficient data transmissions. Combining quantum computing with the IoT improves the system’s performance to a drastic level. The proposed technique focuses on introducing quantum computing into the IoT to optimise the sensor space without degrading the sensing ability of the sensors. To optimise the sensor space, the Quantum Computing based Rider Optimisation (QCRO) is introduced with optimal global search behaviour inspired by the Rider Optimisation Algorithm (ROA). After optimising sensor space, the Glued Tree based on Continuous quantum Walks (GTCW) is used to minimise the energy loss in the network. The continuous quantum walks are introduced into the Glued Trees (GT) to find the optimal path that can provide a minimised error rate. The experimental results demonstrated the effectiveness of the proposed approach against the other existing techniques in terms of data accuracy, data temporal efficiency and data cost.