{"title":"Optimal Update Times for Stale Information Metrics Including the Age of Information","authors":"Chris Ferguson;Leonard Kleinrock","doi":"10.1109/JSAIT.2023.3344760","DOIUrl":null,"url":null,"abstract":"In this paper we examine the general problem of determining when to update information that can go out-of-date. Not updating frequently enough results in poor decision making based on stale information. Updating too often results in excessive update costs. We study the tradeoff between having stale information and the cost of updating that information. We use a general model, some versions of which match an idealized version of the Age of Information (AoI) model. We first present the assumptions, and a novel methodology for solving problems of this sort. Then we solve the case where the update cost is fixed and the time-value of the information is well understood. Our results provide simple and powerful insights regarding optimal update times. We further look at cases where there are delays associated with sending a request for an update and receiving the update, cases where the update source may be stale, cases where the information cannot be used during the update process, and cases where update costs can change randomly.","PeriodicalId":73295,"journal":{"name":"IEEE journal on selected areas in information theory","volume":"4 ","pages":"734-746"},"PeriodicalIF":0.0000,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10371395","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE journal on selected areas in information theory","FirstCategoryId":"1085","ListUrlMain":"https://ieeexplore.ieee.org/document/10371395/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper we examine the general problem of determining when to update information that can go out-of-date. Not updating frequently enough results in poor decision making based on stale information. Updating too often results in excessive update costs. We study the tradeoff between having stale information and the cost of updating that information. We use a general model, some versions of which match an idealized version of the Age of Information (AoI) model. We first present the assumptions, and a novel methodology for solving problems of this sort. Then we solve the case where the update cost is fixed and the time-value of the information is well understood. Our results provide simple and powerful insights regarding optimal update times. We further look at cases where there are delays associated with sending a request for an update and receiving the update, cases where the update source may be stale, cases where the information cannot be used during the update process, and cases where update costs can change randomly.