? 视频数据中心中最小化摄像机流调度的最小开销
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Journal of Computer Science and Technology 2017, Vol. 32 Issue (3) :555-570    DOI: 10.1007/s11390-017-1743-x
Computer Network and Information Security << Previous Articles | Next Articles >>
视频数据中心中最小化摄像机流调度的最小开销
Yi-Hong Gao, Hua-Dong Ma, Fellow, CCF, Wu Liu, Member, CCF
Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, Beijing 100876, China
Minimizing Resource Cost for Camera Stream Scheduling in Video Data Center
Yi-Hong Gao, Hua-Dong Ma, Fellow, CCF, Wu Liu, Member, CCF
Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia, Beijing University of Posts and Telecommunications, Beijing 100876, China

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摘要 视频监控服务可以从IP摄像机处接收直播流,并将这些流转发给终端用户。这类服务正在成为视频数据中心中最受欢迎的服务。视频数据中心需要努力减少为该服务提供资源时的资源开销。然而,现有工作几乎没有充分地考虑上载流与转发流这两个方向的网络带宽开销的优化,并且也没有充分地考虑流媒体服务器的容量限制。本文中,我们提出一个有效的面向在线多摄像机视频转发的资源调度方法。该方法尝试同时优化流媒体服务器与网络资源的共享。首先,我们不仅提供了细粒度的资源使用模型,还同时评估了上载流与转发流的网络带宽开销。为了不失一般性,我们使用了两种资源定价模型,它们分别使用两种不同的资源开销函数来评估资源开销,即线性开销函数和非线性开销函数。之后,我们将资源开销最小化问题建模成约束条件下的整数规划问题。针对线性资源开销函数的情况,一个偏移加惩罚的优化方法被用在我们的调度方法中。针对非线性资源开销函数的情况,我们的资源调度方法使用了一个启发式方法来同时减少流媒体服务器和网络带宽的开销。实验结果表明我们的方法能够显著地减少包含流媒体服务器开销与网络开销在内的资源总开销。
目的:我们考虑上载流与转发流这两个方向的网络带宽开销的优化,并且加入流媒体服务器的服务能力限制。提出一种资源调度方法,在调度资源时减少包括服务器开销与上载、转发网络带宽开销在内的资源总开销。
创新点:提出一种基于“专属+共享”资源槽的上载流调度方法。在响应直播流的上载请求时,视频数据中心需要保证资源的可用性与可扩展性。我们首先使用资源槽的数量表示服务器的服务能力。之后,我们综合考虑了服务器开销与上载、下载阶段的网络开销对资源槽与网络资源的可用性与可扩展性进行建模。基于这些模型,我们分别使用专属调度策略与共享调度策略调节网络开销与服务器开销,达到最小化资源使用开销的目的。
方法:在提供资源的过程中,我们充分考虑了上载与转发带宽开销,并为流媒体服务器提供了一个细粒度的资源使用模型。我们提出的方法,主要最小化流媒体服务器与网络的资源总开销。为了更好地评估流媒体服务器与网络的资源开销,我们使用了不同的定价模型(线性开销模型和非线性开销模型)。在线性开销模型的情况下,我们进一步将这个开销最小化问题建模成约束条件下的整数规划问题。在非线性开销函数(多为凸函数或凹函数)的情况下,由于使用线性开销函数的资源调度方法不能在有效时间内获得最优解。因此,我们进一步提出了一个启发式调度方法来最小化视频数据中心的资源总开销。
结论:本文中,我们在视频数据中心中提出了一个资源开销最小化的方法来提供视频监控即服务。实验结果表明我们的方法可以同时优化流媒体服务器与网络资源的使用。与现有的方法相比,由于我们的方法优化了资源的使用,资源调度器进而能够在不同的资源开销函数以及用户到达模型下达到最小化资源总开销的目标。
关键词视频数据中心   资源调度   视频监控即服务   多摄像机网络     
Abstract: Video surveillance service, which receives live streams from IP cameras and forwards the streams to end users, has become one of the most popular services of video data center. The video data center focuses on minimizing the resource cost during resource provisioning for the service. However, little of the previous work comprehensively considers the bandwidth cost optimization of both upload and forwarding streams, and the capacity of the media server. In this paper, we propose an efficient resource scheduling approach for online multi-camera video forwarding, which tries to optimize the resource sharing of media servers and the networks together. Firstly, we not only provide a fine-grained resource usage model for media servers, but also evaluate the bandwidth cost of both upload and forwarding streams. Without loss of generality, we utilize two resource pricing models with different resource cost functions to evaluate the resource cost: the linear cost function and the non-linear cost functions. Then, we formulate the cost minimization problem as a constrained integer programming problem. For the linear resource cost function, the drift-plus-penalty optimization method is exploited in our approach. For non-linear resource cost functions, the approach employs a heuristic method to reduce both media server cost and bandwidth cost. The experimental results demonstrate that our approach obviously reduces the total resource costs on both media servers and networks simultaneously.
Keywordsvideo data center   resource scheduling   video surveillance as a service   multi-camera networking     
Received 2016-05-20;
本文基金:

The research is supported by the National Natural Science Foundation of China-Guangdong Joint Fund under Grant No. U1501254, the National Natural Science Foundation of China under Grant No. 61332005, the Funds for Creative Research Groups of China under Grant No. 61421061, the Beijing Training Project for the Leading Talents in Science and Technology under Grant No. ljrc 201502, and the Cosponsored Project of Beijing Committee of Education.

About author: Yi-Hong Gao is now a Ph.D. candidate of Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia and the School of Computer Science, Beijing University of Posts and Telecommunications, Beijing. His current research mainly focuses on resource scheduling approach, video data center, cloud computing.
引用本文:   
Yi-Hong Gao, Hua-Dong Ma, Wu Liu.视频数据中心中最小化摄像机流调度的最小开销[J]  Journal of Computer Science and Technology , 2017,V32(3): 555-570
Yi-Hong Gao, Hua-Dong Ma, Wu Liu.Minimizing Resource Cost for Camera Stream Scheduling in Video Data Center[J]  Journal of Computer Science and Technology, 2017,V32(3): 555-570
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http://jcst.ict.ac.cn:8080/jcst/CN/10.1007/s11390-017-1743-x
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