TY - GEN
T1 - Efficient Cloud Computing Resource Management Strategy Based on Auction Mechanism
AU - Chen, Qian
AU - Wang, Xuan
AU - Jiang, Zoe Lin
N1 - Publisher Copyright:
Copyright 2023 KICS.
PY - 2023
Y1 - 2023
N2 - Cloud computing resource management has a crucial position in the cloud computing field, which directly affects the operational performance of various applications and enterprises’ operational efficiency and cost control. It is widely used in many fields, such as big data processing, artificial intelligence, and the Internet of Things. This paper proposes a resource management strategy for cloud computing based on one-price auction and two-price auction mechanisms. First, the critical problem of resource management in cloud computing is abstracted. The strategy based on the auction mechanism is proposed, which improves the space complexity to O(total_length+num_agents) compared with traditional dynamic planning. Secondly, this paper compares the actual computation time of the three methods using polynomial regression, which saves 80% in computation time compared to the dynamic planning algorithm. Finally, the auction mechanism improves the resource allocation rate by 11.93%, while the bivalent auction mechanism reduces the additional cost of computing resources in the cloud platform by 13.89%.
AB - Cloud computing resource management has a crucial position in the cloud computing field, which directly affects the operational performance of various applications and enterprises’ operational efficiency and cost control. It is widely used in many fields, such as big data processing, artificial intelligence, and the Internet of Things. This paper proposes a resource management strategy for cloud computing based on one-price auction and two-price auction mechanisms. First, the critical problem of resource management in cloud computing is abstracted. The strategy based on the auction mechanism is proposed, which improves the space complexity to O(total_length+num_agents) compared with traditional dynamic planning. Secondly, this paper compares the actual computation time of the three methods using polynomial regression, which saves 80% in computation time compared to the dynamic planning algorithm. Finally, the auction mechanism improves the resource allocation rate by 11.93%, while the bivalent auction mechanism reduces the additional cost of computing resources in the cloud platform by 13.89%.
KW - Auction Mechanism
KW - Cloud Computing
KW - Dynamic Programming
KW - Optimization Problem
UR - https://www.scopus.com/pages/publications/85174810543
M3 - 会议稿件
AN - SCOPUS:85174810543
T3 - APNOMS 2023 - 24th Asia-Pacific Network Operations and Management Symposium: Intelligent Management for Enabling the Digital Transformation
SP - 286
EP - 289
BT - APNOMS 2023 - 24th Asia-Pacific Network Operations and Management Symposium
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 24th Asia-Pacific Network Operations and Management Symposium, APNOMS 2023
Y2 - 6 September 2023 through 8 September 2023
ER -