基于带宽请求预测和云资源预留的视频移植策略

doi:10.3969/j.issn.1000-436x.2014.05.022

通信学报 ›› 2014, Vol. 35 ›› Issue (5): 167-174.doi: 10.3969/j.issn.1000-436x.2014.05.022

• 学术通信 • 上一篇

基于带宽请求预测和云资源预留的视频移植策略

丛鑫^1,²,双错¹,苏森¹,杨放春¹,訾玲玲²

¹ 北京邮电大学网络与交换技术国家重点实验室，北京10087
² 辽宁工程技术大学电子与信息工程学院，辽宁葫芦岛125105

出版日期:2014-05-25 发布日期:2017-07-24
基金资助:
中央高校基本科研创新计划专项基金资助项目;国家自然科学基金资助项目;新一代宽带无线移动通信网”科技重大专项基金资助项目;国家重点基础研究发展计划(“973”计划)基金资助项目

Video migration strategy based on bandwidth demand prediction and cloud resource reservation

ONGXin C^1,²,HUANGKai S¹,USen S¹,ANGFang-chun Y¹,ILing-ling Z²

¹ State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
² School of Electronic and Information Engineering, Liaoning Technical University, Huludao 125105, China

Online:2014-05-25 Published:2017-07-24
Supported by:
The Fundamental Research Funds for the Central Universities;The National Natural Science Foundation of China;Important National Science ＆ Technology Specific Projects: Next-generation Broadband Wireless Mobile Communications Network;The National Basic Research Program of China (973 Program)

摘要/Abstract

摘要：

提出云辅助P2P-VoD架构下的视频移植策略。首先根据P2P特性预测每视频频道的用户带宽请求数，为视频移植提供依据。而后设计了最小预留带宽的云带宽资源申请算法，利用较小的开销代价满足VoD服务实时性要求。最后设计了移植策略，决定如何进行视频移植。实验结果表明，提出的策略能够在费用开销和用户满意度之间取得较好的平衡。

关键词: 带宽请求预测, 资源预留, 移植策略, 云辅助P2P-VoD架构

Abstract:

A video migration strategy which is used in P2P-VoD architecture is presented. First it predicts the bandwidth demands of users in each video channel according to the P2P characteristic. And it gives a basis for migrating videos. Then an algorithm of applying cloud resources which is based on the minimum bandwidth reservation is proposed. It sat-isfies the real-time of VoD service with the costs as low as possible. Finally the video migration strategies are designed to determine the methods of migration videos. The simulation results indicate that the proposed strategy can get good trade-off between costs and user satisfaction.

Key words: bandwidth demand prediction, resource reservation, migration strategy, cloud-assisted P2P-VoD

丛鑫,双错,苏森,杨放春,訾玲玲. 基于带宽请求预测和云资源预留的视频移植策略[J]. 通信学报, 2014, 35(5): 167-174.

ONGXin C,HUANGKai S,USen S,ANGFang-chun Y,ILing-ling Z. Video migration strategy based on bandwidth demand prediction and cloud resource reservation[J]. Journal on Communications, 2014, 35(5): 167-174.

图/表 14

表1

图1

图2

图3

图4

图5

图6

表2

图7

图8

图9

图10

图11

图12

参考文献 15

[1]	NIU D , LI B C , ZHAO S Q . Understanding demand volatility in large vod systems[A]. Proceedings of the 21st International Workshop on Network and Operating Systems Support for Digital Audio and Video[C]. 2011. 39-44.
[2]	Youtube homepage[EB/OL]. , 2012.
[3]	YING Q , GUO Y , CHEN Y , et al. nderstanding users' access failure and patience in large-scale P2P VoD systems[A]. Wireless Mobile ＆Multimedia Networks (ICWMMN 2011) 4th IET[C]. 2011. 283-287.
[4]	YouKu[EB/OL]. , 2012.
[5]	APPLEGATE D , ARCHER A , GOPALAKRISHNAN V , et al. Optimal content placement for a large-scale VoD system[A]. ACM CoN-EXT[C]. 2010. 1-12.
[6]	KOREN Y . Factorization meets the neighborhood: a multifaceted collaborative filtering model[A]. Proc of the 14th ACM SIG-KDD Conference[C]. 2008. 426-434.
[7]	NIU D , LI B C , ZHAO S Q . Demand forecast and performance pre-diction in peer-assisted on-demand streaming systems[A]. IEEE Info-com Mini-Conference[C]. 2011. 421-425.
[8]	NIU D , CHEN F , LI B C . A theory of cloud bandwidth pricing for video-on-demand providers[A]. IEEE Infocom[C]. 2012. 711-719.
[9]	Amazon Web services[EB/OL]. .
[10]	BOX G E P , JENKINS G M , REINSEL G C . Time Series Analysis:Forecasting and Control[M]. Wiley, 2008.
[11]	CHAN K S , CRYER J D . Time Series Analysis with Applications in R[M]. Springer, 2008.
[12]	HE H , SIU W C . Single image super-resolution using gaussian process regression[A]. IEEE Computer Vision and Pattern Recognition Con-ference[C]. 2011. 449-456.
[13]	GURSUN G , CROVELLA M , MATTA I . Describing and forecasting video access patterns[A]. INFOCOM Proceedings IEEE 2011[C]. 2011. 16-20.
[14]	LI H , ZHONG L , LIU J , et al. Cost-effective partial migration of VoD services to content clouds[A]. Cloud Computing (CLOUD) 2011 IEEE International Conference on[C]. 2011. 203-210.
[15]	Amazon S3 Pricing[EB/OL]. , 2012.

参数符号	参数含义
N_t	某频道上的在线节点数量
DP_t	下载节点的平均下行带宽
UD_t	下载节点的平均上行带宽
SP_t	对服务器节点请求带宽(上行带宽)
US_t	种子节点的平均上传带宽
R	视频频道的播放速率

参数符号	参数含义
p₁	本地服务器上行带宽单位费用
p₂	云平台下行带宽单位费用
p₃	云平台上行带宽单位费用
p₄	云平台存储单位费用
SP_t(同表1)	对服务器节点请求带宽(上行带宽)
w_i1∈[0,1]	请求分配给本地服务器的权重
w_i2∈[0,1]	请求分配给云平台的权重
b_i	给定SP_ti需要在云平台预留的带宽
B_s(s=1,2)	本地服务器和云平台的最大带宽
v_i	视频i的大小
N	需要移植到云平台的视频个数

基于带宽请求预测和云资源预留的视频移植策略

Video migration strategy based on bandwidth demand prediction and cloud resource reservation

在线阅读

PDF下载

可视化

被引次数

摘要/Abstract

引用本文

使用本文

图/表 14

参考文献 15

相关文章 10

Metrics

推荐阅读 0

[1]	孙国林,欧睿杰,刘贵松. 基于深度强化学习的应急物联网切片资源预留算法[J]. 通信学报, 2020, 41(9): 8-20.
[2]	丁长松,王志英,胡志刚. 基于效用驱动的网格资源协同预留策略[J]. 通信学报, 2014, 35(5): 101-107.
[3]	丛鑫1,2，双锴1，苏森1，杨放春1，訾玲玲2. 基于带宽请求预测和云资源预留的视频移植策略[J]. 通信学报, 2014, 35(5): 22-175.
[4]	丁长松1,2，王志英2，胡志刚3. 基于效用驱动的网格资源协同预留策略[J]. 通信学报, 2014, 35(5): 14-107.
[5]	沈时军1，刘欣然1,2，张鸿1，朱春鸽1,2. 云计算中的服务可用性保障机制[J]. 通信学报, 2014, 35(2): 25-206.
[6]	沈时军,刘欣然,张鸿,朱春鸽. 云计算中的服务可用性保障机制[J]. 通信学报, 2014, 35(2): 202-206.
[7]	张永晖,林漳希,刘建华,梁泉. 基于AAA认证的仓储移动网络安全关联转移方案[J]. 通信学报, 2012, 33(Z1): 186-191.
[8]	丁长松,胡志刚,肖鹏. 网格环境中可靠性增强的资源预留策略[J]. 通信学报, 2011, 32(7): 40-46.
[9]	王贤茜,王淼,陆月明,纪越峰. 串行同源故障通告机制及其在ASON中的应用[J]. 通信学报, 2009, 30(5): 82-87.
[10]	冯美玉,殷贞平,郑敏,丁炜. Ad hoc网络中带宽保证路由协议[J]. 通信学报, 2005, 26(6): 42-48.