DocumentCode
3350889
Title
A general model for resource allocation in utility computing
Author
Zhengyuan Zhou ; Bambos, Nicholas
Author_Institution
Dept. of Electr. Eng., Stanford Univ., Stanford, CA, USA
fYear
2015
fDate
1-3 July 2015
Firstpage
1746
Lastpage
1751
Abstract
A utility computing problem is one in which a server (service provider) provides computing resources to clients (service receivers) whose jobs require the resources for processing. In this paper, we propose a general, decentralized and auction-based model for the server-to-clients resource allocation problem. This model combines a general class of queueing processes with a general class of “incentivecompatible” bidding mechanisms. Crucial to this model is the interplay between the nature of queueing costs and the nature of good bidding mechanisms. Insights on how such interplay contributes to the stability of the system can be helpful in guiding specific implementations in real-world applications. This decentralized and auction-based resource allocation model naturally induces a multi-player game, which is the principal object we study in this paper. We show the existence and uniqueness of Nash equilibrium under this general setting. We also present distributed update dynamics that converge to this unique Nash equilibrium. The distributed dynamics given here share the features of being secure and requiring little communications, thus, providing a practical scheme through which Nash equilibrium is reached.
Keywords
game theory; queueing theory; resource allocation; utility theory; Nash equilibrium; auction-based resource allocation model; decentralized-based resource allocation model; distributed update dynamics; incentive-compatible bidding mechanisms; multiplayer game; queueing costs; queueing processes; server-to-clients resource allocation problem; stability; utility computing problem; Computational modeling; Games; Joints; Nash equilibrium; Resource management; Scalability; Servers;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference (ACC), 2015
Conference_Location
Chicago, IL
Print_ISBN
978-1-4799-8685-9
Type
conf
DOI
10.1109/ACC.2015.7170985
Filename
7170985
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