协作态势驱动的自适应候选者协商维持模型  

Collaboration trend driven adaptive candidate negotiation model

作　　者：封红旗[1] 鞠宏波 张登辉[2] 杨长春[1] FENG Hongqi;JU Hongbo;ZHANG Denghui;YANG Changchun(College of Information Science and Engineering, Changzhou University, Changzhou, Jiangsu 213000, China;College of Information Science, Zhejiang Shuren University, Hangzhou 310000, China)

机构地区：[1]常州大学信息科学与工程学院,江苏常州213000 [2]浙江树人大学信息科技学院,杭州310000

出　　处：《计算机工程与应用》2017年第5期39-44,共6页Computer Engineering and Applications

基　　金：国家自然科学基金(No.61375071);浙江省优先主题重点工业项目(No.2010C11045)

摘　　要：为提高云服务协作过程服务失效的替换成功率,提出一种云平台下协作态势驱动的自适应候选者协商维持模型,利用贝叶斯学习预测协商数据保留值,自适应提交协商议题,以维持与候选者的协商;通过对服务协作过程动态监测,动态优化服务候选集。实验结果表明,服务协商维持模型能适应协作过程变化,使服务协作具有良好的自适应性和健壮性。To improve service to replace the success rate of failure of cloud services collaboration process, it puts forward a collaborative situational evolution based adaptive candidate negotiation model based on cloud platform, uses Bayesian learning forecast consultation data retention value, adaptively submits negotiation issue, in order to maintain negotiate with candidate. Through dynamic monitoring process of service collaboration, it dynamically optimizes service candidates.The experimental results show that maintaining service consultation model can adapt to the collaborative process of change, make the service collaboration with good adaptability and robustness.

关 键 词：云服务 协作 服务失效 协商 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]