Intent-based resource matching strategy in cloud.

Accurate and efficient resource allocation based on user intent is an important issue in a large-scale, distributed environment, such as cloud computing. Although a large number of cloud resource matching models he been proposed, these models do not consider the interests of user and cloud service provider objectively and fairly. Thus, a novel resource matching strategy that regulates multiattribute matching between cloud resources and tasks is proposed in this study. Tasks and resources are initially clustered on the basis of the attribute characteristics to reduce the scope of resource retrieval. Then, the tasks are matched to the appropriate resources in terms of the strict bilateral matching algorithm to improve the satisfaction of both parties. Finally, a series of experiments are reported to show the effectiveness of the algorithm. Experimental results conclusively demonstrate that our proposed methods can availably decrease the scheduling overhead and improve the overall satisfaction of both parties simultaneously. [ABSTRACT FROM AUTHOR]