摘要
保障全局时序的时序约束分解模型(TCD)可以将时序服务组合分解成约束分解与局部优选两个相对独立的过程,但该模型可能丢失可行组合方案,在用户约束强度较强时可能导致无解.该文提出了一种约束强度感知的时序约束分解模型(CIA-TCD),通过在现有的TCD模型中引入松弛因子,使得用户约束强度较弱时,能保证全局约束,而约束强度较强时,也能够保留一定量的组合方案,从而提高找到可行方案的概率.分析表明,当约束强度较强时,CIA-TCD模型较TCD模型找到可行组合方案的概率明显更大.
The temporal constraints decomposition model (TCD), which guarantees the global temporal, can decompose the temporal service composition into two relatively independent processes: constraints decomposition and local optimization. However, the model may lose the feasible combination scheme, which may lead to no solution when the user constraints strength is strong. This paper proposes a constraints strength-aware temporal constraints decomposition model (CIA-TCD), which introduces a relaxation factor into the existing TCD model. When the user constraint strength is weak, the global constraint can be guaranteed;and when the constraint strength is strong, a certain amount of combination scheme can be reserved, thereby increasing the probability that a feasible solution can be found. The experimental analysis shows that the CIA-TCD model has a significantly better probability of finding a feasible combination scheme than the TCD model when the constraint strength is strong.
作者
叶恒舟
胡志丹
YE Heng-zhou;HU Zhi-dan(Guangxi Key Laboratory of Embedded Technology and Intelligent System,Guilin University of Technology Guilin Guangxi 541006)
出处
《电子科技大学学报》
EI
CAS
CSCD
北大核心
2019年第6期880-885,共6页
Journal of University of Electronic Science and Technology of China
基金
国家自然科学基金(51365010)
广西自然科学基金(2014GXNSFBA118269)
关键词
约束分解
约束强度感知
模糊推理
服务组合
时序约束
constraint decomposition
constraint strength-aware
fuzzy inference
service composition
temporal constraint
