QUANTUM-ENHANCED EDGE COMPUTING FOR REAL-TIME DATA PROCESSING IN AUTONOMOUS SYSTEMS

Authors

  • Jain P Department of Computer Science & Engineering Patel College of Science & Technology, Indore (M.P.)

Keywords:

Quantum Computing, Edge Computing, Real-Time Data Processing, Autonomous Systems, Hybrid Computing Architectures

Abstract

The proliferation of Internet of Things (IoT) devices and autonomous systems has necessitated advancements in real-time data processing capabilities. Edge computing addresses latency and bandwidth issues by processing data closer to the source. However, traditional edge computing approaches struggle with the computational demands of complex algorithms, especially in autonomous systems. This paper introduces a novel approach that leverages quantum computing principles to enhance edge computing frameworks. We propose a hybrid architecture combining quantum-enhanced processing units with classical edge nodes to optimize real-time data processing. Our results demonstrate significant improvements in processing speed and efficiency, making this approach viable for deployment in autonomous vehicles and smart city infrastructures.

References

. Nielsen, M.A., & Chuang, I.L. (2010). Quantum Computation and Quantum Information. Cambridge University Press.

. Shi, Y., & Lu, Q. (2018). Edge Computing: A Survey on the State of the Art and Future Directions. IEEE Access, 6, 13-29.

. Arute, F., Arya, K., Babbush, R., & Bacon, D. (2019). Quantum Supremacy Using a Programmable Superconducting Processor. Nature, 574, 505-510.

Downloads

Published

2024-10-03

How to Cite

Jain, P. (2024). QUANTUM-ENHANCED EDGE COMPUTING FOR REAL-TIME DATA PROCESSING IN AUTONOMOUS SYSTEMS. COMPUSOFT: An International Journal of Advanced Computer Technology, 10(00), 3984–3986. Retrieved from https://ijact.in/index.php/j/article/view/618

Issue

Section

Original Research Article

Similar Articles

<< < 21 22 23 24 25 26 27 28 29 30 > >> 

You may also start an advanced similarity search for this article.