The Research On Age-of-Information Optimization Of Multi-Source Information Cache And Update In Internet Of Things

With the continuous development of the Internet of Things(IoT)and 5G communication,there are many time-sensitive applications in reality scenarios.Age of Information(AoI)has become a new performance metric that captures the freshness or timeliness of information at end users in Internet of Things.Most of the existing researches on information updating mechanism mainly consider information updating from a single source node or from multiple source nodes with independent observations.But in the realistic Internet of Things system,each information could be observed by multiple source nodes,which brings new challenges on how to design information transmission or update schemes under the premise of optimizing the information age of content.Different from previous work,we study two information update problems on how to upload or update the contents from source nodes to base station,under the condition that each content can be commonly observed by multiple source nodes.This thesis focuses on AoI-aware Multi-source Information Caching(AoI-MSIC)problem and AoI-aware Multi-source Information Updating(AoI-MSIU)problem.The detailed research contents include the following two aspects:1.For AoI-MSIC problem,is assumed that the contents are the first time to be cached to the base station.A specific mathematical model is established for this problem,and we prove that it is NP-hard.Then an efficient greedy algorithm is proposed,with a guaranteed approximation ratio.Finally,the performance of the proposed algorithm is evaluated through simulation experiments.2.For AoI-MSIU problem,it is assumed that the base station has a certain previous version of the contents.Then we construct an auxiliary bipartite graph between the source node and the information contents,and prove that the maximum weight dichotomous matching of the bipartite graph corresponds to the feasible solution of the original problem.Finally,the performance of the proposed algorithm is evaluated through simulation experiments.