DocumentCode :
2350536
Title :
RAS-M: Resource Allocation Strategy Based on Market Mechanism in Cloud Computing
Author :
You, Xindong ; Xu, Xianghua ; Wan, Jian ; Yu, Dongjin
Author_Institution :
Sch. of Comput. Sci. & Technol., Hangzhou Dianzi Univ., Hangzhou, China
fYear :
2009
fDate :
21-22 Aug. 2009
Firstpage :
256
Lastpage :
263
Abstract :
Resource management is one of the main issues in cloud computing. in order to improve resource utilization of large data centers while delivering services with higher QoS to cloud clients, a resource allocation strategy based on market (RAS-M) is proposed. Firstly, the architecture and the market model of RAS-M are constructed, in which a QoS-refection utility function is designed according to different resource requirements of the cloud client, the equilibrium state of RAS-M is defined and the proof of its optimality is given. Secondly, GA-based price adjusted algorithm is introduced to deal with the problem of achieving the equilibrium state of RAS-M. Finally, RAS-M is implemented upon Xen to reallocate the VM´s weight. Experiments results obtained by setting different parameters show that RAS-M can achieve the equilibrium state approximately, that is, demand and supply is balanced nearly, which validates RAS-M is effective and practicable, and is capable of achieving its goal.
Keywords :
genetic algorithms; grid computing; quality of service; resource allocation; virtual machines; GA-based price adjusted algorithm; QoS-refection utility function; RAS-M; Xen; cloud computing; market mechanism; resource allocation; resource management; resource requirements; virtual machine; Cloud computing; Computational modeling; Computer science; Concurrent computing; Conference management; Distributed computing; Grid computing; Resource management; Technology management; Virtual manufacturing; Cloud Computing; Genetic Algorithm; Market Mechanisml; Resource Allocation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
ChinaGrid Annual Conference, 2009. ChinaGrid '09. Fourth
Conference_Location :
Yantai, Shandong
Print_ISBN :
978-0-7695-3818-1
Type :
conf
DOI :
10.1109/ChinaGrid.2009.41
Filename :
5329054
Link To Document :
بازگشت