中文摘要：

录像监视服务，它现场从 IP 收到流照相机并且提交流终端用户，成为了录像数据中心的最流行的服务之一。最小化资源的录像数据中心焦点为服务在资源期间花费 provisioning。然而，几乎包括地不以前的工作认为带宽是费用优化上载并且提交媒介服务者的溪流，和能力。在这篇论文，我们建议为提交的联机多照相机录像安排途径的一个有效资源，它试着优化媒介分享的资源服务器和网络一起。第一，我们不仅提供一个有细密纹理的资源用法为媒介为服务者建模，而且评估花费的带宽上载并且提交溪流。没有概论的损失，我们利用定价与评估资源的功能花费了的不同资源费用建模的二个资源：线性费用功能和非线性的费用工作。然后，我们作为一个抑制整数编程问题提出花费的最小化问题。为线性资源费用功能， drift-plus-penalty 优化方法在我们的途径被利用。为非线性的资源，费用工作，途径采用一个启发式的方法两个都减少媒介服务器费用和带宽花费了。试验性的结果示威那我们的途径显然减少全部的资源费用上媒介服务者和网络同时。

英文摘要：

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.