摘要
针对传统方法构建的模型寻址规则与逻辑不匹配,导致物联网出现失效节点时模型寻址效果下降,在云信任度评估下,提出全新的物联网海量底层资源寻址模型构建方法。方法预先制定底层寻址编码方案,采用元胞更新模型寻址规则,利用搜索算法设计寻址逻辑,通过建立寻址模型云信任度评估推荐模块,实现对海量底层资源寻址模型的优化。仿真结果表明,与传统寻址模型相比,设计的寻址模型的寻址准确率更高,构建的模型有更好的寻址效果。
In view of the mismatch between the model addressing rules and logic constructed by the traditional method,which leads to the decline of the model addressing effect when there are invalid nodes in the Internet of things,a new method for constructing the addressing model of massive underlying resources in the Internet of things is proposed based on the cloud trust evaluation.Firstly,the underlying addressing coding scheme was formulated.Secondly,cells were applied to update the model addressing rules.Then,the search algorithm was introduced to design the addressing logic.Finally,by establishing the cloud trust evaluation and recommendation module of the addressing model,the optimization of the massive underlying resource addressing model was completed.The simulation results show that the addressing accuracy and effect of this model are better than those of traditional methods.
作者
李波
杨国才
LI Bo;YANG Guo-cai(Chongqing Institute of Engineering,CoUege of Computer and Internet of Things,Chongqing 400056,China;College of Computer&Information Science Southwest University,Chongqing 400715,China)
出处
《计算机仿真》
北大核心
2021年第11期420-423,463,共5页
Computer Simulation
基金
2019年重庆市“一流专业建设”支持项目(渝教高发{2019}7号)
2019年重庆市高等教育教学改革研究项目(192049)
重庆市教育科学规划课题(2018-GX-376)
重庆市教育委员会科学技术研究项目(KJQN201901903)
重庆工程学院教育教学改革研究项目(JY2017205)。
关键词
云信任度评估
物联网
海量底层资源
寻址模型
Cloud trust evaluation
Internet of things
Massive underlying resources
Addressing model
