Xiaoming Yuan, Pengxiang Zhao, Hanyu Hu, Jintao You, Changpeng Yang, Wen Peng, Yonghong Kang, K. M. Teo
{"title":"华为云采用运维研究为直播服务节省网络带宽成本:GSCO 系统","authors":"Xiaoming Yuan, Pengxiang Zhao, Hanyu Hu, Jintao You, Changpeng Yang, Wen Peng, Yonghong Kang, K. M. Teo","doi":"10.1287/inte.2023.0079","DOIUrl":null,"url":null,"abstract":"The rapid evolution of cloud computing technologies has instigated a paradigm shift across various traditional industries, with the live streaming sector standing as a compelling exemplification of this transformation. Huawei Cloud, which has become an influential player in the business-to-business live streaming arena, with its services spanning over 60 countries since 2020, is at the forefront of this shift. Amid the flourishing live streaming market, Huawei Cloud faces the dual challenge of satisfying the escalating demand, while managing the mounting operational costs, predominantly associated with the network bandwidth. To offer premium services while minimizing the bandwidth cost, we developed a dynamic traffic allocation system called GSCO. This system was engineered using an array of operations research methodologies such as continuous optimization, integer programming, graph theory, scheduling, and network-flow problem solving, along with state-of-the-art machine learning algorithms. The GSCO system has been proven highly effective in cost optimization, reducing network bandwidth expenses by about 30% and leading to savings exceeding $49.6 million from Q1 2020 to Q3 2022. In addition, it has significantly bolstered Huawei Cloud’s market share, amplifying peak bandwidth from an initial 1.5 terabits per second (Tbps) to a substantial 16 Tbps.","PeriodicalId":510763,"journal":{"name":"INFORMS Journal on Applied Analytics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Huawei Cloud Adopts Operations Research for Live Streaming Services to Save Network Bandwidth Cost: The GSCO System\",\"authors\":\"Xiaoming Yuan, Pengxiang Zhao, Hanyu Hu, Jintao You, Changpeng Yang, Wen Peng, Yonghong Kang, K. M. Teo\",\"doi\":\"10.1287/inte.2023.0079\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The rapid evolution of cloud computing technologies has instigated a paradigm shift across various traditional industries, with the live streaming sector standing as a compelling exemplification of this transformation. Huawei Cloud, which has become an influential player in the business-to-business live streaming arena, with its services spanning over 60 countries since 2020, is at the forefront of this shift. Amid the flourishing live streaming market, Huawei Cloud faces the dual challenge of satisfying the escalating demand, while managing the mounting operational costs, predominantly associated with the network bandwidth. To offer premium services while minimizing the bandwidth cost, we developed a dynamic traffic allocation system called GSCO. This system was engineered using an array of operations research methodologies such as continuous optimization, integer programming, graph theory, scheduling, and network-flow problem solving, along with state-of-the-art machine learning algorithms. The GSCO system has been proven highly effective in cost optimization, reducing network bandwidth expenses by about 30% and leading to savings exceeding $49.6 million from Q1 2020 to Q3 2022. In addition, it has significantly bolstered Huawei Cloud’s market share, amplifying peak bandwidth from an initial 1.5 terabits per second (Tbps) to a substantial 16 Tbps.\",\"PeriodicalId\":510763,\"journal\":{\"name\":\"INFORMS Journal on Applied Analytics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"INFORMS Journal on Applied Analytics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1287/inte.2023.0079\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"INFORMS Journal on Applied Analytics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1287/inte.2023.0079","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Huawei Cloud Adopts Operations Research for Live Streaming Services to Save Network Bandwidth Cost: The GSCO System
The rapid evolution of cloud computing technologies has instigated a paradigm shift across various traditional industries, with the live streaming sector standing as a compelling exemplification of this transformation. Huawei Cloud, which has become an influential player in the business-to-business live streaming arena, with its services spanning over 60 countries since 2020, is at the forefront of this shift. Amid the flourishing live streaming market, Huawei Cloud faces the dual challenge of satisfying the escalating demand, while managing the mounting operational costs, predominantly associated with the network bandwidth. To offer premium services while minimizing the bandwidth cost, we developed a dynamic traffic allocation system called GSCO. This system was engineered using an array of operations research methodologies such as continuous optimization, integer programming, graph theory, scheduling, and network-flow problem solving, along with state-of-the-art machine learning algorithms. The GSCO system has been proven highly effective in cost optimization, reducing network bandwidth expenses by about 30% and leading to savings exceeding $49.6 million from Q1 2020 to Q3 2022. In addition, it has significantly bolstered Huawei Cloud’s market share, amplifying peak bandwidth from an initial 1.5 terabits per second (Tbps) to a substantial 16 Tbps.