Please use this identifier to cite or link to this item: http://localhost/handle/Hannan/655738
Title: Resource Allocation With Video Traffic Prediction in Cloud-Based Space Systems
Authors: Jun Du;Chunxiao Jiang;Yi Qian;Zhu Han;Yong Ren
subject: Space-based information network|resource allocation|video traffic prediction
Year: 2016
Publisher: IEEE
Abstract: This paper considers the resource allocation problems for video transmission in space-based information networks. The queueing system analyzed in this study is constituted by multiple users and a single server. The server is operated as a cloud that can sense the traffic arrivals to each user's queue and then allocates the transmission resource and service rate for users. The objectives are to make configurations over time to minimize the time average cost of the system, and to minimize the waiting time of packets after they enter the queue. Meanwhile, the constraints on the queue stability of the system must be satisfied. In this paper, we introduce a predictive backpressure algorithm, which considers the future arrivals with a certain prediction window size into the consideration of resource allocation to make decisions on which packets to be served first. In addition, this paper designs a multiresolution wavelet decomposition-based backpropagation network for the prediction of video traffic, which exhibits the long-range dependence property. Simulation results indicate that the delay of the queueing system can be reduced through this prediction-based resource allocation, and the prediction accuracy for the video traffic is improved according to the proposed prediction system.
URI: http://localhost/handle/Hannan/160254
http://localhost/handle/Hannan/655738
ISSN: 1520-9210
1941-0077
volume: 18
issue: 5
Appears in Collections:2016

Files in This Item:
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Title: Resource Allocation With Video Traffic Prediction in Cloud-Based Space Systems
Authors: Jun Du;Chunxiao Jiang;Yi Qian;Zhu Han;Yong Ren
subject: Space-based information network|resource allocation|video traffic prediction
Year: 2016
Publisher: IEEE
Abstract: This paper considers the resource allocation problems for video transmission in space-based information networks. The queueing system analyzed in this study is constituted by multiple users and a single server. The server is operated as a cloud that can sense the traffic arrivals to each user's queue and then allocates the transmission resource and service rate for users. The objectives are to make configurations over time to minimize the time average cost of the system, and to minimize the waiting time of packets after they enter the queue. Meanwhile, the constraints on the queue stability of the system must be satisfied. In this paper, we introduce a predictive backpressure algorithm, which considers the future arrivals with a certain prediction window size into the consideration of resource allocation to make decisions on which packets to be served first. In addition, this paper designs a multiresolution wavelet decomposition-based backpropagation network for the prediction of video traffic, which exhibits the long-range dependence property. Simulation results indicate that the delay of the queueing system can be reduced through this prediction-based resource allocation, and the prediction accuracy for the video traffic is improved according to the proposed prediction system.
URI: http://localhost/handle/Hannan/160254
http://localhost/handle/Hannan/655738
ISSN: 1520-9210
1941-0077
volume: 18
issue: 5
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7423764.pdf1.24 MBAdobe PDFThumbnail
Preview File
Title: Resource Allocation With Video Traffic Prediction in Cloud-Based Space Systems
Authors: Jun Du;Chunxiao Jiang;Yi Qian;Zhu Han;Yong Ren
subject: Space-based information network|resource allocation|video traffic prediction
Year: 2016
Publisher: IEEE
Abstract: This paper considers the resource allocation problems for video transmission in space-based information networks. The queueing system analyzed in this study is constituted by multiple users and a single server. The server is operated as a cloud that can sense the traffic arrivals to each user's queue and then allocates the transmission resource and service rate for users. The objectives are to make configurations over time to minimize the time average cost of the system, and to minimize the waiting time of packets after they enter the queue. Meanwhile, the constraints on the queue stability of the system must be satisfied. In this paper, we introduce a predictive backpressure algorithm, which considers the future arrivals with a certain prediction window size into the consideration of resource allocation to make decisions on which packets to be served first. In addition, this paper designs a multiresolution wavelet decomposition-based backpropagation network for the prediction of video traffic, which exhibits the long-range dependence property. Simulation results indicate that the delay of the queueing system can be reduced through this prediction-based resource allocation, and the prediction accuracy for the video traffic is improved according to the proposed prediction system.
URI: http://localhost/handle/Hannan/160254
http://localhost/handle/Hannan/655738
ISSN: 1520-9210
1941-0077
volume: 18
issue: 5
Appears in Collections:2016

Files in This Item:
File Description SizeFormat 
7423764.pdf1.24 MBAdobe PDFThumbnail
Preview File