引用本文:江琦,奚宏生,殷保群.无线多媒体通信网适应带宽配置在线优化算法.软件学报,2007,18(6):1491-1500
【打印本页】   【下载PDF全文】   查看/发表评论  【EndNote】   【RefMan】   【BibTex】
←前一篇|后一篇→ 过刊浏览    高级检索
本文已被:浏览 4898次   下载 6645 本文二维码信息
码上扫一扫!
分享到: 微信 更多
无线多媒体通信网适应带宽配置在线优化算法
江琦1, 奚宏生1, 殷保群1
中国科学技术大学,自动化系,安徽,合肥,230027
摘要:
基于强化学习的方法,提出一种无线多媒体通信网适应带宽配置在线优化算法,在满足多类业务不同QoS(quality of service)要求的同时,提高网络资源的利用率.建立事件驱动的随机切换分析模型,将无线多媒体通信网中的适应带宽配置问题转化为带约束的连续时间Markov决策问题.利用此模型的动态结构特性,结合在线学习估计梯度与随机逼近改进策略,提出适应带宽配置在线优化算法.该算法不依赖于系统参数,如呼叫到达率、呼叫持续时间等,自适应性强,计算量小,能够收敛到全局最优,适用于复杂应用环境中无线多媒体通信网适应带宽配置的在线优化.仿真实验结果验证了算法的有效性.
关键词:  适应带宽配置  Markov决策过程  策略优化  强化学习  随机逼近  QoS(quality of service)保证
DOI:
分类号:
基金项目:Supported by the National Natural Science Foundation of China under Grant No.60574065 (国家自然科学基金); the National High-Tech Research and Development Plan of China under Grant No.2006AA01Z114 (国家高技术研究发展计划(863)); the Natural Science Foundation of Anhui Province of China under Grant Nos.050420301, 070412063 (安徽省自然科学基金); the Graduate Student Innovation Foundation of USTC under Grant No.KD2006036 (中国科学技术大学研究生创新基金)
An Online Adaptive Bandwidth Allocation Optimization Algorithm for Wireless Multimedia Communication Networks
JIANG Qi,XI Hong-Sheng,YIN Bao-Qun
Abstract:
The issue of QoS (quality of service) provisioning for adaptive multimedia in wireless communication networks is considered. A reinforcement learning based online adaptive bandwidth allocation optimization algorithm is proposed. First, an event-driven stochastic switching model is introduced to formulate the adaptive bandwidth allocation problem as a constrained continuous-time Markov decision problem. Then, an online optimization algorithm that combines policy gradient estimation by learning and stochastic approximation is derived. This algorithm can online handle the constrained optimization problem efficiently without explicit knowledge of the underlying system parameters. Moreover, this algorithm does not require the computation of performance potentials or other related quantities (e.g. Q-factors), which is necessary in previous schemes, and therefore saves computational cost significantly. Simulation results demonstrate the effectiveness of the proposed algorithm.
Key words:  adaptive bandwidth allocation  Markov decision processes  policy optimization  reinforcement learning  stochastic approximation  QoS (quality of service) provisioning

引用本文:
【打印本页】   【下载PDF全文】   查看/发表评论  【EndNote】   【RefMan】   【BibTex】
←前一篇|后一篇→ 过刊浏览    高级检索
本文已被:浏览次   下载  
分享到: 微信 更多
摘要:
关键词:  
DOI:
分类号:
基金项目:
Abstract:
Key words: