An effective method for service components selection based on micro-canonical annealing considering dependability assurance
An effective method for service components selection based on micro-canonical annealing considering dependability assurance
复制标题
考虑可靠性保证的基于微规范退火的有效服务组件选择方法
DOI：
10.1007/s11704-017-6317-0
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发表时间：
2019-04
影响因子：
4.2
通讯作者：
Feng Guangsheng
中科院分区：
文献类型：
--
作者：
Zou Shichen;Lin Junyu;Wang Huiqiang;Lv Hongwu;Feng Guangsheng
分布式虚拟化改变了构建软件系统的模式。然而，由于服务组件之间复杂的社会关系和交互，给可靠性保证带来了一些问题。在分布式虚拟化环境中，解决这些问题的最好方法是选择可靠的服务组件。依赖服务组件的选择可以建模为寻找一条可靠的服务路径，这是一个多约束的最优路径问题。本文从可信性保证的角度出发，提出了一种在分布式虚拟化环境中寻找可信服务路径的服务组件选择方法。引入可信性质量的概念来描述和约束动态组合过程中软件系统的可信性。然后，将可靠服务组件选择问题建模为多约束最优路径问题，采用自适应加罚微正则退火算法求解最优可靠服务路径，实验结果表明，该算法具有较高的搜索成功率和较快的收敛速度。
Distributed virtualization changes the pattern of building software systems. However, it brings some problems on dependability assurance owing to the complex social relationships and interactions between service components. The best way to solve the problems in a distributed virtualized environment is dependable service components selection. Dependable service components selection can be modeled as finding a dependable service path, which is a multiconstrained optimal path problem. In this paper, a service components selection method that searches for the dependable service path in a distributed virtualized environment is proposed from the perspective of dependability assurance. The concept of Quality of Dependability is introduced to describe and constrain software system dependability during dynamic composition. Then, we model the dependable service components selection as a multiconstrained optimal path problem, and apply the Adaptive Bonus-Penalty Microcanonical Annealing algorithm to find the optimal dependable service path. The experimental results show that the proposed algorithm has high search success rate and quick converges.
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影响因子：
3.7
作者：
Zibin Zheng;Michael R. Lyu
通讯作者：
Zibin Zheng;Michael R. Lyu
DOI：
10.1016/j.physa.2013.01.035
发表时间：
2013-05
期刊：
Physica A: Statistical Mechanics and its Applications
影响因子：
--
作者：
Li, Hui1;Zhao, Hai1;Cai, Wei1;Xu, Jiu-Qiang1;Ai, Jun1
通讯作者：
Ai, Jun1
影响因子：
8.6
作者：
CREUTZ, M
通讯作者：
CREUTZ, M
影响因子：
11.8
作者：
Shuiguang Deng;Longtao Huang;Ying Li;Honggeng Zhou;Zhaohui Wu;Xiongfei Cao;M. Kataev;L. Li
通讯作者：
Shuiguang Deng;Longtao Huang;Ying Li;Honggeng Zhou;Zhaohui Wu;Xiongfei Cao;M. Kataev;L. Li
DOI：
10.1145/2109205.2109206
发表时间：
2012-03
期刊：
ACM Trans. Web
影响因子：
--
作者：
Guangyu Zhu;G. Mishne
通讯作者：
Guangyu Zhu;G. Mishne