Back to Search Start Over

Performance Analysis of a Keyword-Based Trust Management System for Fog Computing.

Authors :
Alwakeel, Ahmed M.
Source :
Applied Sciences (2076-3417); Aug2023, Vol. 13 Issue 15, p8714, 24p
Publication Year :
2023

Abstract

This study presents a novel keyword-based trust management system for fog computing networks aimed at improving network efficiency and ensuring data integrity. The proposed system establishes and maintains trust between fog nodes using trust keywords recorded in a table on each node. Simulation research is conducted using iFogSim to evaluate the efficacy of the proposed scheme in terms of latency and packet delivery ratio. The study focuses on addressing trust and security challenges in fog computing environments. By leveraging trust keywords, the proposed system enables accurate evaluation of trustworthiness and identification of potentially malicious nodes. The system enhances the security of fog computing by mitigating risks associated with unauthorized access and malicious behavior. While the study highlights the significance of trust keywords in improving network performance and trustworthiness, it fails to provide detailed explanations of the trust mechanism itself. Additionally, the role of fog computing in the proposed approach is not adequately emphasized. Future research directions include refining and optimizing the proposed framework to consider resource constraints, dynamic network conditions, and scalability. Integration of advanced security mechanisms such as encryption and authentication protocols will be explored to strengthen the trust foundation in fog computing environments. In conclusion, the proposed keyword-based trust management system offers potential benefits for improving network performance and ensuring data integrity in fog computing. However, further clarification of the trust mechanism and a stronger emphasis on the role of fog computing would enhance understanding of the proposed approach. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
20763417
Volume :
13
Issue :
15
Database :
Complementary Index
Journal :
Applied Sciences (2076-3417)
Publication Type :
Academic Journal
Accession number :
169910220
Full Text :
https://doi.org/10.3390/app13158714