Xiaocui Sun, Zhijun Wang, Yunxiang Wu, Hao Che, Hong Jiang
{"title":"PACCP:数据中心的价格感知拥塞控制协议","authors":"Xiaocui Sun, Zhijun Wang, Yunxiang Wu, Hao Che, Hong Jiang","doi":"10.1109/UCC48980.2020.00022","DOIUrl":null,"url":null,"abstract":"To date, customers using infrastructure-as-a service (IaaS) cloud services are charged for the usage of computing/storage resources, but not the network resource. The difficulty lies in the fact that it is nontrivial to allocate network resource to individual customers effectively, especially for short-lived flows, in terms of both performance and cost. To tackle this challenge, in this paper, we propose PACCP, an end-to-end Price-Aware Congestion Control Protocol for cloud services. PACCP is a network utility maximization (NUM) based optimal congestion control protocol. It supports three different classes of services (CoSes), i.e., best effort service (BE), differentiated service (DS), and minimum rate guaranteed (MRG) service. In PACCP, the desired CoS or rate allocation for a given flow is enabled by properly setting a pair of control parameters, i.e., a minimum guaranteed rate and a utility weight, which in turn, determines the price paid by the user of the flow. Two pricing models, i.e., a coarse-grained Virtual machine (VM)-Based Pricing model (VBP) and a fine-grained Flow-Based Pricing model (FBP), are proposed. PACCP is evaluated by both large scale simulation and small testbed implementation. The results demonstrate that PACCP provides minimum rate guarantee, high bandwidth utilization and fair rate allocation, commensurate with the pricing models.","PeriodicalId":125849,"journal":{"name":"2020 IEEE/ACM 13th International Conference on Utility and Cloud Computing (UCC)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"PACCP: A Price-Aware Congestion Control Protocol for Datacenters\",\"authors\":\"Xiaocui Sun, Zhijun Wang, Yunxiang Wu, Hao Che, Hong Jiang\",\"doi\":\"10.1109/UCC48980.2020.00022\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To date, customers using infrastructure-as-a service (IaaS) cloud services are charged for the usage of computing/storage resources, but not the network resource. The difficulty lies in the fact that it is nontrivial to allocate network resource to individual customers effectively, especially for short-lived flows, in terms of both performance and cost. To tackle this challenge, in this paper, we propose PACCP, an end-to-end Price-Aware Congestion Control Protocol for cloud services. PACCP is a network utility maximization (NUM) based optimal congestion control protocol. It supports three different classes of services (CoSes), i.e., best effort service (BE), differentiated service (DS), and minimum rate guaranteed (MRG) service. In PACCP, the desired CoS or rate allocation for a given flow is enabled by properly setting a pair of control parameters, i.e., a minimum guaranteed rate and a utility weight, which in turn, determines the price paid by the user of the flow. Two pricing models, i.e., a coarse-grained Virtual machine (VM)-Based Pricing model (VBP) and a fine-grained Flow-Based Pricing model (FBP), are proposed. PACCP is evaluated by both large scale simulation and small testbed implementation. The results demonstrate that PACCP provides minimum rate guarantee, high bandwidth utilization and fair rate allocation, commensurate with the pricing models.\",\"PeriodicalId\":125849,\"journal\":{\"name\":\"2020 IEEE/ACM 13th International Conference on Utility and Cloud Computing (UCC)\",\"volume\":\"118 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE/ACM 13th International Conference on Utility and Cloud Computing (UCC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/UCC48980.2020.00022\",\"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/ACM 13th International Conference on Utility and Cloud Computing (UCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/UCC48980.2020.00022","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
PACCP: A Price-Aware Congestion Control Protocol for Datacenters
To date, customers using infrastructure-as-a service (IaaS) cloud services are charged for the usage of computing/storage resources, but not the network resource. The difficulty lies in the fact that it is nontrivial to allocate network resource to individual customers effectively, especially for short-lived flows, in terms of both performance and cost. To tackle this challenge, in this paper, we propose PACCP, an end-to-end Price-Aware Congestion Control Protocol for cloud services. PACCP is a network utility maximization (NUM) based optimal congestion control protocol. It supports three different classes of services (CoSes), i.e., best effort service (BE), differentiated service (DS), and minimum rate guaranteed (MRG) service. In PACCP, the desired CoS or rate allocation for a given flow is enabled by properly setting a pair of control parameters, i.e., a minimum guaranteed rate and a utility weight, which in turn, determines the price paid by the user of the flow. Two pricing models, i.e., a coarse-grained Virtual machine (VM)-Based Pricing model (VBP) and a fine-grained Flow-Based Pricing model (FBP), are proposed. PACCP is evaluated by both large scale simulation and small testbed implementation. The results demonstrate that PACCP provides minimum rate guarantee, high bandwidth utilization and fair rate allocation, commensurate with the pricing models.