{"title":"An auto-adjustment cache algorithm in handheld learning devices","authors":"Liang Peng, Yan-li Xu","doi":"10.1109/ICICISYS.2009.5358225","DOIUrl":null,"url":null,"abstract":"There are many challenges of using all kinds of handheld devices as learning tools, that can connect to the Remote Learning System by cable or wireless network and then browser the downloaded course contents. First of all, network connection, especially wireless link, is usually not persistent and wireless coverage is often limited. In this case, the handheld learning devices become useless and the learning activities are interfered. Secondly, the learning resource size become more and more large, so that the time to wait for these resources downloaded from the remote learning system would be more and more long. Thirdly, computing power and storages ability of the device is too weak to save or perform plentiful downloaded learning resource. In order to solute the mentioned problems, an auto-adjustment cache algorithm is purposed in a Remote Learning System.","PeriodicalId":206575,"journal":{"name":"2009 IEEE International Conference on Intelligent Computing and Intelligent Systems","volume":"89 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Conference on Intelligent Computing and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICISYS.2009.5358225","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
There are many challenges of using all kinds of handheld devices as learning tools, that can connect to the Remote Learning System by cable or wireless network and then browser the downloaded course contents. First of all, network connection, especially wireless link, is usually not persistent and wireless coverage is often limited. In this case, the handheld learning devices become useless and the learning activities are interfered. Secondly, the learning resource size become more and more large, so that the time to wait for these resources downloaded from the remote learning system would be more and more long. Thirdly, computing power and storages ability of the device is too weak to save or perform plentiful downloaded learning resource. In order to solute the mentioned problems, an auto-adjustment cache algorithm is purposed in a Remote Learning System.