通信学报2026，Vol.47Issue(7)：1-15,15.DOI:10.11959/j.issn.1000-436x.TXXB260195
基于主动推理的拟态云服务多余度裁决在线自适应优化算法
Online adaptive optimization algorithm for redundancy adjudication in mimic cloud services based on active inference
摘要
Abstract
To address the problem that redundancy adjudication parameter configuration in mimic cloud services is diffi-cult to adapt to dynamic environments,and that security gain,service latency,and recovery effectiveness are difficult to optimize jointly,an active inference-based online adaptive optimization(AIOAO)algorithm was proposed.Firstly,for mimic cloud services,a quantitative mapping model between adjudication parameters and security gain,service latency,and recovery effectiveness was established,and the adjudication parameter configuration was formulated as a multi-objective online optimization problem in a dynamic and uncertain environment.Secondly,the AIOAO algorithm was pro-posed,in which an active inference mechanism was introduced to adaptively update adjudication parameters online.Ex-perimental results show that the AIOAO algorithm can dynamically adjust adjudication parameters according to system state changes,and improve security gain and recovery effectiveness while keeping service latency under control.关键词
拟态云服务/多余度裁决/主动推理Key words
mimic cloud service/redundancy adjudication/active inference分类
信息技术与安全科学引用本文复制引用
张乾坤,刘冰,盛章骏,邓贤君,袁斌,张帅,梁浩,程国振,丁国栋..基于主动推理的拟态云服务多余度裁决在线自适应优化算法[J].通信学报,2026,47(7):1-15,15.基金项目
国家自然科学基金资助项目(No.62302183) （No.62302183）
网络空间安全教育部重点实验室开放基金资助项目(No.KLCS20240401)The National Natural Science Foundation of China(No.62302183),The Open Foundation of Key Laboratory of Cyberspace Security,Ministry of Education of China(No.KLCS20240401) （No.KLCS20240401）
