Meitian Huang, W. Liang, Zichuan Xu, M. Jia, Song Guo
{"title":"Throughput Maximization in Software-Defined Networks with Consolidated Middleboxes","authors":"Meitian Huang, W. Liang, Zichuan Xu, M. Jia, Song Guo","doi":"10.1109/LCN.2016.58","DOIUrl":null,"url":null,"abstract":"Today's computer networks rely on a wide spectrum of specialized middleboxes to improve their security and performance. Traditional middleboxes that are implemented by dedicated hardware are expensive and hard to manage. A promising technique of consolidated middleboxes - implementing traditional middleboxes in Virtual Machines (VMs) - offers economical yet simplified management of middleboxes in Software-Defined Networks (SDNs). However there are still challenges to realizing user routing requests with network function enforcement (a sequence of middleboxes) while maximizing the network throughput, due to various resource constraints on SDNs, such as forwarding table capacity at each switch, bandwidth resource capacity at each link, and computing resource capacity at each server (Physical Machine). In this paper, we study the problem of maximizing the network throughput of an SDN by admitting as many user requests as possible, where each user request has both bandwidth and computing resource demands to implement its network functions (consolidated middleboxes). We first formulate the problem as a novel network throughput maximization problem. We then provide an Integer Linear Program (ILP) solution for it if the problem size is small, otherwise, we devise two heuristics that strive for the fine tradeoff between the accuracy of solutions and the running times of achieving the solutions. We finally evaluate the performance of the proposed algorithms by simulations, based on real and synthetic network topologies. Experimental results demonstrate that the proposed algorithms are very promising.","PeriodicalId":6864,"journal":{"name":"2016 IEEE 41st Conference on Local Computer Networks (LCN)","volume":"66 1","pages":"298-306"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE 41st Conference on Local Computer Networks (LCN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/LCN.2016.58","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 21
Abstract
Today's computer networks rely on a wide spectrum of specialized middleboxes to improve their security and performance. Traditional middleboxes that are implemented by dedicated hardware are expensive and hard to manage. A promising technique of consolidated middleboxes - implementing traditional middleboxes in Virtual Machines (VMs) - offers economical yet simplified management of middleboxes in Software-Defined Networks (SDNs). However there are still challenges to realizing user routing requests with network function enforcement (a sequence of middleboxes) while maximizing the network throughput, due to various resource constraints on SDNs, such as forwarding table capacity at each switch, bandwidth resource capacity at each link, and computing resource capacity at each server (Physical Machine). In this paper, we study the problem of maximizing the network throughput of an SDN by admitting as many user requests as possible, where each user request has both bandwidth and computing resource demands to implement its network functions (consolidated middleboxes). We first formulate the problem as a novel network throughput maximization problem. We then provide an Integer Linear Program (ILP) solution for it if the problem size is small, otherwise, we devise two heuristics that strive for the fine tradeoff between the accuracy of solutions and the running times of achieving the solutions. We finally evaluate the performance of the proposed algorithms by simulations, based on real and synthetic network topologies. Experimental results demonstrate that the proposed algorithms are very promising.