Distributed resource allocation for data center networks: a hierarchical game approach

Zhang, H., Xiao, Y., Bu, S. , Yu, R., Niyato, D. and Han, Z. (2020) Distributed resource allocation for data center networks: a hierarchical game approach. IEEE Transactions on Cloud Computing, 8(3), pp. 778-789. (doi: 10.1109/TCC.2018.2829744)

Abstract

The increasing demand of data computing and storage for cloud-based services motivates the development and deployment of large-scale data centers. This paper studies the resource allocation problem for the data center networking system when multiple data center operators (DCOs) simultaneously serve multiple service subscribers (SSs). We formulate a hierarchical game to analyze this system where the DCOs and the SSs are regarded as the leaders and followers, respectively. In the proposed game, each SS selects its serving DCO with preferred price and purchases the optimal amount of resources for the SS's computing requirements. Based on the responses of the SSs' and the other DCOs', the DCOs decide their resource prices so as to receive the highest profit. When the coordination among DCOs is weak, we consider all DCOs are noncooperative with each other, and propose a sub-gradient algorithm for the DCOs to approach a sub-optimal solution of the game. When all DCOs are sufficiently coordinated, we formulate a coalition game among all DCOs and apply Kalai-Smorodinsky bargaining as a resource division approach to achieve high utilities. Both solutions constitute the Stackelberg Equilibrium. The simulation results verify the performance improvement provided by our proposed approaches.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Bu, Dr Shengrong
• Authors: Zhang, H., Xiao, Y., Bu, S., Yu, R., Niyato, D., and Han, Z.
• College/School: College of Science and Engineering > School of Engineering > Systems Power and Energy
• Journal Name: IEEE Transactions on Cloud Computing
• Publisher: IEEE
• ISSN: 2168-7161
• ISSN (Online): 2168-7161
• Published Online: 24 April 2018
• Copyright Holders: Copyright © 2018 IEEE
• First Published: First published in IEEE Transactions on Cloud Computing 8(3): 778-789
• Publisher Policy: Reproduced in accordance with the copyright policy of the publisher