Task scheduling algorithm based on security and trusted monitoring of domestic Kunpeng architecture processor

Yifan Liu; Junnan Liu; Xin He

doi:10.1117/12.2691837

23 August 2023 Task scheduling algorithm based on security and trusted monitoring of domestic Kunpeng architecture processor

Yifan Liu, Junnan Liu, Xin He

Author Affiliations +

Proceedings Volume 12784, Second International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2023); 127843B (2023) https://doi.org/10.1117/12.2691837
Event: 2023 2nd International Conference on Applied Statistics, Computational Mathematics and Software Engineering (ASCMSE 2023), 2023, Kaifeng, China

Abstract

With the development of computer technology, people have higher and higher requirements for computer performance and reliability and security of system operation. Heterogeneous multi-core processor, as a new type of computer processor, has the ability to switch tasks between different types of cores, which provides more space and possibility for realizing the efficient operation of computer system, improving the computing power and enhancing the security of the system. In this paper, the task scheduling algorithm of heterogeneous multi-core processor will be discussed, and its relationship with virtual execution environment and security domain will be explored. This paper combines heterogeneous multi-core processor task scheduling algorithm with three-domain separation of multi-level security and trusted monitoring method to propose an effective scheme to improve the security of computer systems. The combination of security monitoring mechanisms in different fields can effectively prevent all kinds of security problems, so as to ensure the normal operation of computer system and data security.

Citation Download Citation

Yifan Liu, Junnan Liu, and Xin He "Task scheduling algorithm based on security and trusted monitoring of domestic Kunpeng architecture processor", Proc. SPIE 12784, Second International Conference on Applied Statistics, Computational Mathematics, and Software Engineering (ASCMSE 2023), 127843B (23 August 2023); https://doi.org/10.1117/12.2691837

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available