Library-Abstract-UNITED SOCIETIES OF SCIENCE

Home / USS Digital Library / Article / Details

Banking System with Deadlock Detection and Avoidance

Publisher: IEEE

Authors: K Saravanan, SRM IST Trichy

Favorite
Share:

Abstract:

Deadlock prevention and avoidance are critical challenges in operating systems and resource management. Traditional algorithms like the Banker's Algorithm provide theoretical solutions but lack predictive capabilities and real-time risk assessment. This paper presents an advanced deadlock avoidance system that integrates machine learning with classical resource management techniques.The implementation features a comprehensive graphical interface visualizing resource allocation graphs, safety sequences, and risk metrics. Experimental results demonstrate that our ML-enhanced approach can predict deadlocks with up to 87% accuracy, providing early warnings that enable proactive resource management decisions. This hybrid approach bridges the gap between theoretical deadlock avoidance and practical system implementation, offering a more intelligent and adaptive solution for modern computing environments.

Keywords: Deadlock avoidance,Machine learning,Resource allocation,Banker’s Algorithm,Operating systems,Predictive modeling

Published in: 2024 Asian Conference on Communication and Networks (ASIANComNet)

Date of Publication: --

DOI: -

Publisher: IEEE

ABSTRACT LIBRARY

Banking System with Deadlock Detection and Avoidance

Publisher: IEEE

Abstract:

USS WeChat Official Account