Hongli Xu, Jinyuan Fan, Jianhuai Wu, C. Qiao, Liusheng Huang
{"title":"Joint deployment and routing in hybrid SDNs","authors":"Hongli Xu, Jinyuan Fan, Jianhuai Wu, C. Qiao, Liusheng Huang","doi":"10.1109/IWQoS.2017.7969133","DOIUrl":null,"url":null,"abstract":"To take advantage of software defined networking (SDN) within a limited budget constraint, a natural strategy is to incrementally deploy a few SDN switches (and a limited amount of additional link bandwidth) into the legacy optical network. In such a hybrid optical network, operators can only change the routes of flows that traverse SDN switches. Therefore, to optimize SDN deployment, it is essential to decide the best places to deploy SDN resources (including SDN switches and link bandwidth) while taking the network traffic into consideration. In this paper, we propose a new SDN deployment scheme, called duplicated deployment, to provide a simple and efficient way for a hybrid network. Based on the proposed deployment scheme, we for the first time define the joint duplicated deployment and routing (DDR) problem for throughput maximization (or optimal deployment) with a given budget constraint on the additional SDN resource cost. Due to the NP-Hardness of the DDR problem, we then present an approximation algorithm based on the traffic mapping and randomized rounding methods, and prove that the approximation factor is (O(log n);O(log n)) in the worst case and (O(1);O(1)) under most practical situations for link capacity and flow-table size constraints, where n is the number of devices (including SDN switches and legacy routers) in the hybrid network. Through extensive simulations, we demonstrate high efficiency of our joint deployment and routing algorithm. For example, our proposed algorithm can improve the network throughput by about 26% compared with existing routing mechanisms with the same amount of extra resources.","PeriodicalId":422861,"journal":{"name":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE/ACM 25th International Symposium on Quality of Service (IWQoS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWQoS.2017.7969133","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 11
Abstract
To take advantage of software defined networking (SDN) within a limited budget constraint, a natural strategy is to incrementally deploy a few SDN switches (and a limited amount of additional link bandwidth) into the legacy optical network. In such a hybrid optical network, operators can only change the routes of flows that traverse SDN switches. Therefore, to optimize SDN deployment, it is essential to decide the best places to deploy SDN resources (including SDN switches and link bandwidth) while taking the network traffic into consideration. In this paper, we propose a new SDN deployment scheme, called duplicated deployment, to provide a simple and efficient way for a hybrid network. Based on the proposed deployment scheme, we for the first time define the joint duplicated deployment and routing (DDR) problem for throughput maximization (or optimal deployment) with a given budget constraint on the additional SDN resource cost. Due to the NP-Hardness of the DDR problem, we then present an approximation algorithm based on the traffic mapping and randomized rounding methods, and prove that the approximation factor is (O(log n);O(log n)) in the worst case and (O(1);O(1)) under most practical situations for link capacity and flow-table size constraints, where n is the number of devices (including SDN switches and legacy routers) in the hybrid network. Through extensive simulations, we demonstrate high efficiency of our joint deployment and routing algorithm. For example, our proposed algorithm can improve the network throughput by about 26% compared with existing routing mechanisms with the same amount of extra resources.