DocumentCode :
3279840
Title :
A Framework to Provide Trust and Incentive in CROWN Grid for Dynamic Resource Management
Author :
Zhang, Yu ; Jinpeng Huai ; Liu, Yunhao ; Lin, Li ; Yang, Baaian
Author_Institution :
Dept. of Comput. Sci. & Techonology, Beihang Univ., Beijing
fYear :
2006
fDate :
9-11 Oct. 2006
Firstpage :
390
Lastpage :
395
Abstract :
In order to maximize resource utilization as well as providing trust management in grid, we propose a novel framework - Trust-Incentive Resource Management (TIM). Having child model, club model, bid model and trust model, TIM dynamically manages grid resource by integrating values of prices, trust, and incentive. In this mechanism, providers set the price according to demand and supply, and consumers maximize the surplus upon budget and deadline. A weighted voting scheme is also proposed to secure the grid system by declining the join request from malicious nodes. A TIM prototype has been successfully implemented in a real grid system, CROWN grid. We evaluate the proposed approach through comprehensive experiments and achieve improved results in resource allocation efficiency, system completion time, and aggregated resource utilization.
Keywords :
grid computing; resource allocation; security of data; CROWN grid computing environment; bid model; child model; club model; dynamic grid resource management; resource allocation; resource utilization maximization; secure grid system; trust model; trust-incentive resource management; weighted voting scheme; Aggregates; Collaboration; Environmental economics; Incentive schemes; Peer to peer computing; Prototypes; Resource management; Security; Supply and demand; Voting; CROWN; incentive; resource allocation; trust;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Communications and Networks, 2006. ICCCN 2006. Proceedings.15th International Conference on
Conference_Location :
Arlington, VA
ISSN :
1095-2055
Print_ISBN :
1-4244-0572-6
Type :
conf
DOI :
10.1109/ICCCN.2006.286307
Filename :
4067688
Link To Document :
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