| 事件驱动的动态服务组合策略在线自适应优化 |
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| 引用本文： | 江琦,奚宏生,殷保群. 事件驱动的动态服务组合策略在线自适应优化[J]. 控制理论与应用, 2011, 28(8): 1049-1055 |
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| 作者姓名： | 江琦 奚宏生 殷保群 |
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| 作者单位： | 1. 合肥工业大学电气与自动化工程学院,安徽合肥230009／中国科学技术大学自动化系,安徽合肥230027
2. 中国科学技术大学自动化系,安徽合肥,230027 |
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| 基金项目： | 国家自然科学基金资助项目(60774038, 60904021, 61074033); 国家“863”计划资助项目(2008AA01A317); 中国博士后科学基金资助项目(20090450820); 博士学科点专项科研基金资助项目(20093402110019); 安徽省自然科学基金资助项目(11040606M142). |
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| 摘 要： | 针对复杂应用环境中网络新媒体服务系统的特点，提出一种事件驱动的动态服务组合策略及其在线优化算法，在保证各类业务服务质量（QoS）的同时，提高系统资源的利用率．通过定义不同类型的事件，驱动服务组合的动态调整，实现对各类业务Qos的保障和对业务需求变化的感知．构建基于半Markov切换空间控制过程的系统分析模型，利用模型的动态结构特点，提出一种结合随机逼近和策略迭代的在线优化算法．该算法不依赖系统参数信息，对环境具有良好的自适应性．仿真实验结果验证了算法的有效性．
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| 关 键 词： | 动态服务组合 层次化Markov控制过程 策略迭代 服务覆盖网络 优化算法 |
| 收稿时间： | 2010-01-28 |
| 修稿时间： | 2010-11-29 |
Online adaptive optimization for event-driven dynamic service composition |
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| JIANG Qi,XI Hong-sheng and YIN Bao-qun. Online adaptive optimization for event-driven dynamic service composition[J]. Control Theory & Applications, 2011, 28(8): 1049-1055 |
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| Authors: | JIANG Qi XI Hong-sheng YIN Bao-qun |
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| Affiliation: | School of Electrical Engineering and Automation, Hefei University of Technology; Department of Automation, University of Science and Technology of China,Department of Automation, University of Science and Technology of China,Department of Automation, University of Science and Technology of China |
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| Abstract: | An event-driven dynamic service composition strategy is presented for networked new media service systems to improve the resource utilization while simultaneously ensuring the quality of service(QoS) for multi-class services. An analytical model of semi-Markov switching state-space control processes is introduced to formulate the dynamic service composition problem. By utilizing the dynamic hierarchy of this model and the features of event-driven policy, an online optimization algorithm that combines stochastic approximation with the policy iteration is proposed. This algorithm is independent of any prior knowledge of system parameters and is with less computational cost. Simulation results demonstrate the effectiveness of the proposed algorithm. |
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| Keywords: | dynamic service composition hierarchical Markov control processes policy iteration service overlay networks optimization algorithm |
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