具有统一中间盒的软件定义网络中的吞吐量最大化

Meitian Huang, W. Liang, Zichuan Xu, M. Jia, Song Guo
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引用次数: 21

摘要

今天的计算机网络依赖于广泛的专用中间体来提高其安全性和性能。由专用硬件实现的传统中间件价格昂贵且难以管理。一种很有前途的整合中间件技术——在虚拟机(vm)中实现传统的中间件——在软件定义网络(sdn)中提供经济而简化的中间件管理。然而,由于sdn上的各种资源限制,例如每个交换机的转发表容量、每个链路的带宽资源容量和每个服务器(物理机)的计算资源容量,在最大限度地提高网络吞吐量的同时,通过网络功能强制实现用户路由请求仍然存在挑战。在本文中,我们研究了通过允许尽可能多的用户请求来最大化SDN网络吞吐量的问题,其中每个用户请求都有带宽和计算资源需求来实现其网络功能(合并中间盒)。我们首先将该问题表述为一个新的网络吞吐量最大化问题。然后,如果问题规模较小,我们将为其提供整数线性规划(ILP)解决方案,否则,我们将设计两种启发式方法,力求在解决方案的准确性和实现解决方案的运行时间之间进行良好的权衡。最后,我们通过基于真实和合成网络拓扑的仿真来评估所提出算法的性能。实验结果表明,该算法是很有前途的。
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Throughput Maximization in Software-Defined Networks with Consolidated Middleboxes
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.
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