Resource Allocation in Cloud Environment: A Model Based on Double Multi-attribute Auction Mechanism

Author

Xingwei Wang ; Xueyi Wang ; Cho-Li Wang ; Keqin Li ; Min Huang

Author_Institution

Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China

fYear

2014

fDate

15-18 Dec. 2014

Firstpage

599

Lastpage

604

Abstract

In this paper, a resource allocation model is constructed, based on the Double Multi-Attribute Auction (DMAA) mechanism. Firstly, multiple attributes are taken into account to form the Quality Index (QI), which is used to comprehensively evaluate consumers´ and providers´ performance in the transactions. Secondly, a Support Vector Machine (SVM) algorithm is adopted to predict the price. Finally, the Mean-Variance Optimization (MVO) algorithm is solved to obtain the optimized resource allocation scheme. Simulation results show that the proposed model can improve the resource utilization while satisfying user needs better.

Keywords

cloud computing; resource allocation; support vector machines; DMAA mechanism; MVO algorithm; QI; SVM algorithm; cloud environment; consumer performance evaluation; double multiattribute auction mechanism; mean-variance optimization algorithm; optimized resource allocation scheme; provider performance evaluation; quality index; resource allocation model; support vector machine algorithm; Computational modeling; Prediction algorithms; Quality of service; Resource management; Sociology; Statistics; Support vector machines; double multi-attribute auction mechanism; mean-variance optimization; price prediction; quality index; resource allocation;

fLanguage

English

Publisher

ieee

Conference_Titel

Cloud Computing Technology and Science (CloudCom), 2014 IEEE 6th International Conference on

Conference_Location

Singapore

Type

conf

DOI

10.1109/CloudCom.2014.103

Filename

7037722