{"title":"普适学习中的蚁类课件查找","authors":"Xiao Zheng, F. Luo","doi":"10.1109/ICCSE.2009.5228421","DOIUrl":null,"url":null,"abstract":"This paper proposes a novel distributed courseware lookup method in pervasive learning environments. This method is based on the concepts of social relationship overlay and pheromone-based ant-like query routing. It exploits an ant-like query routing mechanism, which views query messages as artificial ants, and utilizes pheromone as routing hints that direct query messages to nodes owning more courseware. This paper presents generation and update rule of pheromone, routing policy for artificial ants as well. In order to avoid getting into local optimization, the roulette wheel technique is used in routing policy. Our method supports high mobility and is suitable for pervasive learning networks. By adjusting the number of artificial ants dynamically, a better tradeoff between cost and quality could be achieved.","PeriodicalId":303484,"journal":{"name":"2009 4th International Conference on Computer Science & Education","volume":"8 4","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Ant-like courseware lookup in pervasive learning\",\"authors\":\"Xiao Zheng, F. Luo\",\"doi\":\"10.1109/ICCSE.2009.5228421\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a novel distributed courseware lookup method in pervasive learning environments. This method is based on the concepts of social relationship overlay and pheromone-based ant-like query routing. It exploits an ant-like query routing mechanism, which views query messages as artificial ants, and utilizes pheromone as routing hints that direct query messages to nodes owning more courseware. This paper presents generation and update rule of pheromone, routing policy for artificial ants as well. In order to avoid getting into local optimization, the roulette wheel technique is used in routing policy. Our method supports high mobility and is suitable for pervasive learning networks. By adjusting the number of artificial ants dynamically, a better tradeoff between cost and quality could be achieved.\",\"PeriodicalId\":303484,\"journal\":{\"name\":\"2009 4th International Conference on Computer Science & Education\",\"volume\":\"8 4\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-07-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 4th International Conference on Computer Science & Education\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCSE.2009.5228421\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 4th International Conference on Computer Science & Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSE.2009.5228421","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
This paper proposes a novel distributed courseware lookup method in pervasive learning environments. This method is based on the concepts of social relationship overlay and pheromone-based ant-like query routing. It exploits an ant-like query routing mechanism, which views query messages as artificial ants, and utilizes pheromone as routing hints that direct query messages to nodes owning more courseware. This paper presents generation and update rule of pheromone, routing policy for artificial ants as well. In order to avoid getting into local optimization, the roulette wheel technique is used in routing policy. Our method supports high mobility and is suitable for pervasive learning networks. By adjusting the number of artificial ants dynamically, a better tradeoff between cost and quality could be achieved.