A fine-grained flow control model for cloud-assisted data broadcasting
Authors: 
Ning Yu, Feng Gu, Xuan Guo, Zaobo HeAuthors Info & Claims
Abstract
Cloud-assisted data broadcasting is an emerging application where cloud computing assists data broadcasting to extend the capacity of system computing and improve the interactivity of the conventional media. However, with the increase in scale, it brings the difficulty on the complexity to provide the sufficient quality of service for diverse receivers. In order to obtain a fine-grained flow rate as well as the system stability, we propose a model based on parallel scheduling, fair queue and Proportional-Integral-Derivative (PID) controller to cope with these challenges. PID controller takes advantage of the feedback of the statistical output stream and automatically adjusts the transmission flow so that the system can achieve the fine-grained multiplexing performance. Meanwhile, we adopt a set of novel metrics to monitor and measure the quality of flow control in order to weaken the negative impact of coarse-grained flow to user-end devices to the minimum level. Extensive simulations and evaluations have illustrated the superiority of the proposed model in the performance and the quality of service in terms of proposed measurement metrics.
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Index Terms
- A fine-grained flow control model for cloud-assisted data broadcasting
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Published: 12 April 2015
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