摘要
提出一种可信的自适应服务组合机制.首先,将组合服务的可信性保证问题转换为自适应控制问题,可信性保证策略作为可调节控制器,组合服务作为被控对象,并设计了相应的系统结构;其次,在马尔可夫决策过程框架下建模和优化组合服务的可信维护过程和策略,并设计了相应的算法,实现了基于强化学习的直接自适应控制机制;最后,通过仿真实验,将组合服务的自适应维护与随机维护策略比较,表明组合服务的自适应维护具有明显的优越性.
Service composition which integrates the functionalities of different services is a promising technique for developing applications especially for across multiple organizations. The dependability of Web services, however, is limited in some important ways for the distributed, dynamic and autonomous service domains. This paper addresses this problem by proposing dependable and adaptive approach for Service Composition. This paper initially transforms the composite services dependability maintain problem to a adaptive control problem, modeling the control process as a Markov decision process and therefore, it proposes an adaptive control system architecture, then designs and optimizes the maintenance strategy in accordance with control goals given in the setting of the theory of Markov Decision Process. It further gives Reinforcement Learning Based Adaptive Control Mechanism and corresponding algorithm to maintain the dependability of composite service. Finally this paper implements a prototype system to evaluate the proposed approach through comprehensive experiments and achieves improved results.
出处
《计算机学报》
EI
CSCD
北大核心
2008年第8期1434-1444,共11页
Chinese Journal of Computers
基金
国家自然科学基金(60525209)
国家"八六三"高技术研究发展计划项目基金(2006AA01Z19A
2007AA010301)
国家"九七三"重点基础研究发展规划项目基金(2005CB321803)资助~~
关键词
服务组合
可信性
自适应控制
强化学习
Q学习算法
service composition
dependability
adaptive control
reinforcement learning
Q learning algorithm
