System for Performing Resource Management and Control and Task Scheduling in Grid Computing

Author(s):  
Fan Yu-tao ◽  
Yu Sheng-chen ◽  
Xue Yang
2011 ◽  
Vol 50-51 ◽  
pp. 526-530 ◽  
Author(s):  
Xiao Bo Gao

From the perspective of resource sharing, grid computing is a system ranging from small kind of network system for home using to large-scale network computing systems even to the Internet. The management of resources in the grid environment becomes very complex as these resources are distributed geographically, heterogeneous in nature, and each having their own resource management policies and different access as well as cost models. In this paper, we bring forward an efficient resources management model and task scheduling algorithm in grid computing. The simulation results show that the proposed algorithm achieves resource load balancing, and can be applied to the optimization of task scheduling successfully.


2010 ◽  
Vol 129-131 ◽  
pp. 1438-1443
Author(s):  
Chen Qi ◽  
Hou Ming

Combining with the advantages of ant colony algorithm to solve optimization problem, this paper designs a grid resource allocation model and task scheduling system based on ant colony algorithm. The algorithm can not only locally update for the pheromone in the allocation of grid computing resources, but also can entirely update for the pheromone after the completion of grid computing resources. Experimental results show that the ant colony algorithm can effectively achieve a reasonable task scheduling and load balancing, its application in the task scheduling in grid environment is very successful.


2012 ◽  
Vol 263-266 ◽  
pp. 1892-1896
Author(s):  
Fu Fang Li ◽  
Dong Qing Xie ◽  
Ying Gao ◽  
Guo Wen Xie ◽  
Qiu Ye Guo

Multi-QoS and Trusted resource management and Task Scheduling are key problem in cloud computing. This paper presented an effective Multi-QoS and Trusted resource management model and Task Scheduling algorithm in Cloud Computing Environment. By using the idea of fuzzy clustering for reference, the proposed approach can subtly schedule the Cloud tasks to appropriate resources that exactly meets its’ multi-QoS needs of resources. Considering the credibility of cloud resources, the credibility and trusty of task scheduling has been dramatically improved.


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