ISSN 1000-1239 CN 11-1777/TP

• 软件技术 •

### 面向环境与需求不确定性的系统自适应决策

1. 1(高可信软件技术教育部重点实验室(北京大学) 北京 100871); 2(中国科学院数学与系统科学研究院数学研究所 北京 100190); 3(北京大学信息科学技术学院软件研究所 北京 100871) (zhuoqun.y@hotmail.com)
• 出版日期: 2018-05-01
• 基金资助:
国家“九七三”重点基础研究发展计划基金项目(2015CB352200);国家自然科学基金项目(61620106007)

### Self-Adaptive Decision Making Under Uncertainty in Environment and Requirements

Yang Zhuoqun2,Jin Zhi1,3

1. 1(Key Laboratory of High Confidence Software Technologies (Peking University), Ministry of Education, Beijing 100871); 2(Institute of Mathematics, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190); 3(Insitute of Software, School of Electronics Engineering and Computer Science, Peking University, Beijing 100871)
• Online: 2018-05-01

Abstract: Software systems intensively interact with other software/hardware systems, devices and users. The operation environment of software becomes unstable and software requirements may also change. Due to the fact that it is hard to predict the environment and requirements at runtime, their changes become uncertain. For providing continuous service, software systems need to adjust themselves according to changes in the environment and themselves. Uncertainties bring great challenges to the adaptation process. Existing related efforts either target at modeling the effects on requirements caused by environmental changes, or focus on how to adjust software behaviors to satisfy fixed requirements under changing environment. With these approaches, it is difficult to deal with the variability and complexity in the adaptation process when requirements are uncertain. This paper proposes a fuzzy control based adaptation decision-making approach, to tackling environment and requirements uncertainties at runtime. It applies fuzzy logic to model and specify variables existing in the environment and software, and generates reasoning rules between variables; designs the adaptation mechanism based on the feedforward-feedback control structure and fuzzy controllers; implements decision-making through fuzzy inference and genetic algorithm. The adaptation results under different environment and constraints show that software can achieve the optimal decision with the adaptation mechanism and algorithms. The feasibility and effectiveness of the approach are illustrated through a mobile bitcoin-miner system.