Rama Ferguson, Brody Voth, Zachary di Giovanni, Diego Felix de Almeida, Michal Aibin
{"title":"内容交付网络的蜜蜂算法","authors":"Rama Ferguson, Brody Voth, Zachary di Giovanni, Diego Felix de Almeida, Michal Aibin","doi":"10.1109/CCECE47787.2020.9255719","DOIUrl":null,"url":null,"abstract":"The rapid changes and increase of modern and cloud-ready services “on-demand” increase the utilization of Content Delivery Networks (CDNs) to deliver service and content to end-users efficiently. In order to minimize the communication cost and the average waiting time, it is necessary to send the end-users' requests to the best available servers. In this paper, we design and implement a Honeybee algorithm that adapts quickly to possible servers' downtime to avoid communication delays. We then compare it to other algorithms available in the literature. Finally, the evaluation is performed using various scenarios with networking issues, such as single server failures or natural disasters consisting of multiple server issues.","PeriodicalId":296506,"journal":{"name":"2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Honeybee Algorithm for Content Delivery Networks\",\"authors\":\"Rama Ferguson, Brody Voth, Zachary di Giovanni, Diego Felix de Almeida, Michal Aibin\",\"doi\":\"10.1109/CCECE47787.2020.9255719\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The rapid changes and increase of modern and cloud-ready services “on-demand” increase the utilization of Content Delivery Networks (CDNs) to deliver service and content to end-users efficiently. In order to minimize the communication cost and the average waiting time, it is necessary to send the end-users' requests to the best available servers. In this paper, we design and implement a Honeybee algorithm that adapts quickly to possible servers' downtime to avoid communication delays. We then compare it to other algorithms available in the literature. Finally, the evaluation is performed using various scenarios with networking issues, such as single server failures or natural disasters consisting of multiple server issues.\",\"PeriodicalId\":296506,\"journal\":{\"name\":\"2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCECE47787.2020.9255719\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCECE47787.2020.9255719","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The rapid changes and increase of modern and cloud-ready services “on-demand” increase the utilization of Content Delivery Networks (CDNs) to deliver service and content to end-users efficiently. In order to minimize the communication cost and the average waiting time, it is necessary to send the end-users' requests to the best available servers. In this paper, we design and implement a Honeybee algorithm that adapts quickly to possible servers' downtime to avoid communication delays. We then compare it to other algorithms available in the literature. Finally, the evaluation is performed using various scenarios with networking issues, such as single server failures or natural disasters consisting of multiple server issues.