视频云网平台中涵盖了大量智能算法,如何对其进行高效管理,从而支持应用服务的快速部署与更新是一个重要的科学问题.然而,传统的智能算法与云端资源具有绑定规则,不同应用服务商之间的智能算法缺乏统一的调用机制,导致它们无法快速整合...视频云网平台中涵盖了大量智能算法,如何对其进行高效管理,从而支持应用服务的快速部署与更新是一个重要的科学问题.然而,传统的智能算法与云端资源具有绑定规则,不同应用服务商之间的智能算法缺乏统一的调用机制,导致它们无法快速整合和有效利用.为了解决此难题,建立“服务—算法—资源”动态互联服务体系,有效解决算法快速迭代、应用需求时变与智能算法版权固化管理的矛盾.在动态互联服务过程中,传统的、面向固定内容的买断式数字版权管理已经无法为细粒度权限管理提供高效服务.为此,提出智能算法版权管理系统(algorithmic intelligence right management,AIRM),通过设计版权资源服务化方法与流动性算力网络结构,构建视频云网平台中“共享式”智能算法版权管理方法.在中国电信视频分析平台授权管理模块中的实际部署结果表明,所设计方法可以将算法并发服务能力提高19.9倍,将算法版权响应时间降低18.36%.展开更多
In order to make full use of the radio resource of heterogeneous wireless networks（HWNs） and promote the quality of service（Qo S） of multi-homing users for video communication, a bandwidth allocation algorithm bas...In order to make full use of the radio resource of heterogeneous wireless networks（HWNs） and promote the quality of service（Qo S） of multi-homing users for video communication, a bandwidth allocation algorithm based on multi-radio access is proposed in this paper. The proposed algorithm adopts an improved distributed common radio resource management（DCRRM） model which can reduce the signaling overhead sufficiently. This scheme can be divided into two phases. In the first phase, candidate network set of each user is obtained according to the received signal strength（RSS）. And the simple additive weighted（SAW） method is employed to determine the active network set. In the second phase, the utility optimization problem is formulated by linear combining of the video communication satisfaction model, cost model and energy efficiency model. And finding the optimal bandwidth allocation scheme with Lagrange multiplier method and Karush-Kuhn-Tucker（KKT） conditions. Simulation results show that the proposed algorithm promotes the network load performances and guarantees that users obtain the best joint utility under current situation.展开更多
文摘视频云网平台中涵盖了大量智能算法,如何对其进行高效管理,从而支持应用服务的快速部署与更新是一个重要的科学问题.然而,传统的智能算法与云端资源具有绑定规则,不同应用服务商之间的智能算法缺乏统一的调用机制,导致它们无法快速整合和有效利用.为了解决此难题,建立“服务—算法—资源”动态互联服务体系,有效解决算法快速迭代、应用需求时变与智能算法版权固化管理的矛盾.在动态互联服务过程中,传统的、面向固定内容的买断式数字版权管理已经无法为细粒度权限管理提供高效服务.为此,提出智能算法版权管理系统(algorithmic intelligence right management,AIRM),通过设计版权资源服务化方法与流动性算力网络结构,构建视频云网平台中“共享式”智能算法版权管理方法.在中国电信视频分析平台授权管理模块中的实际部署结果表明,所设计方法可以将算法并发服务能力提高19.9倍,将算法版权响应时间降低18.36%.
基金supported by the National Natural Science Foundation of China (61571234, 61401225)the National Basic Research Program of China (2013CB329005)+1 种基金the Hi-Tech Research and Development Program of China (2014AA01A705)the Graduate Student Innovation Plan of Jiangsu Province (SJLX15_0365)
文摘In order to make full use of the radio resource of heterogeneous wireless networks（HWNs） and promote the quality of service（Qo S） of multi-homing users for video communication, a bandwidth allocation algorithm based on multi-radio access is proposed in this paper. The proposed algorithm adopts an improved distributed common radio resource management（DCRRM） model which can reduce the signaling overhead sufficiently. This scheme can be divided into two phases. In the first phase, candidate network set of each user is obtained according to the received signal strength（RSS）. And the simple additive weighted（SAW） method is employed to determine the active network set. In the second phase, the utility optimization problem is formulated by linear combining of the video communication satisfaction model, cost model and energy efficiency model. And finding the optimal bandwidth allocation scheme with Lagrange multiplier method and Karush-Kuhn-Tucker（KKT） conditions. Simulation results show that the proposed algorithm promotes the network load performances and guarantees that users obtain the best joint utility under current situation.
基金Supported by the National Grand Fundamental Research 973 Program of China under Grant No.G1998030405 (国家重点基础研究发展规划(973)) the Beijing Committee of Science and Technology under Grand No.H011710010123 (北京市科学技术委员会资助项目)
