基于多路径路由的IP网流量工程问题研究
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摘要
传统的Web业务、流行的流媒体业务、以及新兴的云计算业务持续增长,促使IP网流量不断增加。流量的激增和突发影响了网络的服务质量,直接的结果就是运营商对网络不间断的扩容。但服务质量问题并未彻底解决,而网络资源也并未有效利用,由此,对网络流量工程的研究应运而生,并得到了学术界的广泛关注。
路由优化在流量工程中充当了关键角色：发现源一目的(Origin-Destination)对间的多条路径,并在多路径间引导流量分布。多路径方式的路由优化算法可在多条可用路径间灵活分配流量,使网络变得更加高效和可靠。本论文研究了当前业界的主要流量工程技术,提出了多路径路由下的最优流量均衡模型,在流量请求未知情形下,分别提出了ISP骨干网和数据中心网络中的多路径构建和流量分布算法。本论文主要做了如下工作：
(一)网络流量工程进展的研究。对当前的流量工程方法做了汇总,从不同角度探讨了当前存在于IP网络中的技术实现。首先探讨了公开的研究性网络数据,其次,按路由范围分别讨论域内和域间的流量工程机制,以及进一步的路由算法。然后,从另外的视角重新审视现有的流量工程方法。多角度的归纳和解析,潜在地影响了流量工程方法的创新。最后,讨论了数据中心网络环境下的流量工程问题。
(二)最小化路径代价和流量均衡模型及实现算法。以最小化网络拥塞为目的,指出网络拥塞决定于流量路由时所选路径的拥塞特征后,建立了流量分布的最小化路径代价和模型。在流量路由选择路径时,提出基于瓶颈链路的最小代价路径路由算法。在实际的网络拓扑和流量矩阵数据基础上对所提模型及算法进行了实验验证,结果显示：在网络负载较大时最大链路利用率相对于已有模型可降低近20%。
(三)最小割多路径路由算法。基于最小割理论,提出了最小割多路径(MCMP)路由算法,为流量请求选取少量关键路径,并在这些路径间均衡流量,在获得方法易实现性的同时能有效控制网络瓶颈链路拥塞。通过实际流量数据在北美和欧洲骨干网络中的实验,对比常用的OSPF路由算法和模型中的多路径路由算法,MCMP路由算法可降低拥塞链路负载分别达到41%和20%以上。
(四)数据中心网络中大流碰撞回避多路径路由算法。因数据中心支持服务的种类和规模日益增长,数据中心中大流普遍存在；而传统的路由算法,无法解决大流的碰撞问题。提出了大流碰撞回避算法,预先计算的可回避碰撞的路径组,作为路由大流的主路径,并以低概率选择备用路径均衡流量。实验验证该多路径路由算法优于数据中心网络中典型的传统路由算法。大流碰撞回避算法无需网络状态数据,更适于分布式部署。
Traditional web services, prevailing streaming media services and growing cloud computing services enforce a huge increase in traffic volume. The traffic increase with bursts frequently influences network performance, causing IP network providers to overprovision in their networks. However, this approach still cannot satisfy the demand from sharply growing customer traffic, while the network resources are not used efficiently. Therefore, traffic engineering is put forward for network optimization, and becomes a research focus.
Routing optimization plays a key role in traffic engineering, finding multiple paths between source-destination pairs, and directing traffic on them. Optimized multi-path routing divides traffic flows flexibly between available paths, making network more efficient and robust. Today's mainstream traffic engineering mechanisms in industry are reviewed; optimal load balancing model for multi-path routing are proposed; without knowledge of traffic matrix, multiple paths seeking and traffic distributing algorithms are proposed in ISP backbone network and data center network separately. The main contributions are as follows.
(1) On the Development of Network Traffic Engineering. Methods employed in today's traffic engineering are put together, and their implementations in IP network are classified for investigating from various aspects. First, public network data for research purposes, topology inclusive, are examined. Second, from an aspect of routing extent, intra-domain and inter-domain traffic engineering mechanisms are introduced; routing algorithms under these topics are also involved. Finally, new aspects are applied to review traffic engineering methods mentioned. Collecting and analyzing existing ones in various ways potentially lead to creative methods. Finally, traffic engineering in data center network is also reviewed.
(2) Minimizing Sum of Path-cost Model and Algorithm for Traffic Balancing. Traffic balancing in routing optimization problem targets to minimize network congestion in traffic engineering. How to select paths for traffic balancing becomes a challenging problem. For minimizing network congestion, the paper argues that network congestion is determined by paths'congestion, and proposes the minimizing sum of path-cost model of traffic balancing. For path selection in routing traffic, a minimal cost path algorithm is proposed. On the basis of real network topology and traffic demand, experiments are conducted to verify the model and algorithm proposed, and results show a nearly20%decrease of maximal link utilization.
(3) Min-Cut Multi-Path Routing Algorithm. Balanced traffic distribution can be archived through traffic engineering, and therefore network congestion is avoided. Today, routing through multiple paths to balance traffic distribution becomes a traffic engineering focus. As enforced by the restrictions of current routing mechanisms, existing multi-path routing algorithms could not get optimal traffic distribution, and therefore could not control network congestion efficiently. On the basis of minimum cut theory, the paper propose a min-cut multi-path (MCMP) routing algorithm, which select key paths of small quantity and distribute traffic evenly among selected paths. MCMP is apt to implement and control congestion at bottleneck links. With real traffic datasets, experiments are carried on European and North American backbone networks. Comparing to OSPF routing algorithm used in intra-domain network and a multiple paths routing algorithm used in optimal model, the maximum link load resulted from MCMP routing algorithm decreases over41%and20%separately.
(4) Big-Flow Collision Avoidance Multi-Path Routing Algorithm in Data Center Network. To accommodate demand's variation and network's scalability, traffic engineering in data center has become an interesting focus in research field. As services supported by data center proliferate in diversity and in extent, big flows herein are popular; however, traditional routing algorithms cannot afford to resolve the collision problem of the flows. The paper propose an collision avoidance algorithm for the problem mentioned; the algorithm finds a path set in advance, primary routes for delivering big flows, and secondary routes for sharing traffic load simultaneously. Experiments carried out in typical data center topology exhibit that the proposed algorithm performs well in reducing maximum link load of core links, as opposed to traditional routing algorithms. Our collision avoidance algorithm is suited for deploying in distributed manner, since its nature of not concerning network status.
路由优化在流量工程中充当了关键角色：发现源一目的(Origin-Destination)对间的多条路径,并在多路径间引导流量分布。多路径方式的路由优化算法可在多条可用路径间灵活分配流量,使网络变得更加高效和可靠。本论文研究了当前业界的主要流量工程技术,提出了多路径路由下的最优流量均衡模型,在流量请求未知情形下,分别提出了ISP骨干网和数据中心网络中的多路径构建和流量分布算法。本论文主要做了如下工作：
(一)网络流量工程进展的研究。对当前的流量工程方法做了汇总,从不同角度探讨了当前存在于IP网络中的技术实现。首先探讨了公开的研究性网络数据,其次,按路由范围分别讨论域内和域间的流量工程机制,以及进一步的路由算法。然后,从另外的视角重新审视现有的流量工程方法。多角度的归纳和解析,潜在地影响了流量工程方法的创新。最后,讨论了数据中心网络环境下的流量工程问题。
(二)最小化路径代价和流量均衡模型及实现算法。以最小化网络拥塞为目的,指出网络拥塞决定于流量路由时所选路径的拥塞特征后,建立了流量分布的最小化路径代价和模型。在流量路由选择路径时,提出基于瓶颈链路的最小代价路径路由算法。在实际的网络拓扑和流量矩阵数据基础上对所提模型及算法进行了实验验证,结果显示：在网络负载较大时最大链路利用率相对于已有模型可降低近20%。
(三)最小割多路径路由算法。基于最小割理论,提出了最小割多路径(MCMP)路由算法,为流量请求选取少量关键路径,并在这些路径间均衡流量,在获得方法易实现性的同时能有效控制网络瓶颈链路拥塞。通过实际流量数据在北美和欧洲骨干网络中的实验,对比常用的OSPF路由算法和模型中的多路径路由算法,MCMP路由算法可降低拥塞链路负载分别达到41%和20%以上。
(四)数据中心网络中大流碰撞回避多路径路由算法。因数据中心支持服务的种类和规模日益增长,数据中心中大流普遍存在；而传统的路由算法,无法解决大流的碰撞问题。提出了大流碰撞回避算法,预先计算的可回避碰撞的路径组,作为路由大流的主路径,并以低概率选择备用路径均衡流量。实验验证该多路径路由算法优于数据中心网络中典型的传统路由算法。大流碰撞回避算法无需网络状态数据,更适于分布式部署。
Traditional web services, prevailing streaming media services and growing cloud computing services enforce a huge increase in traffic volume. The traffic increase with bursts frequently influences network performance, causing IP network providers to overprovision in their networks. However, this approach still cannot satisfy the demand from sharply growing customer traffic, while the network resources are not used efficiently. Therefore, traffic engineering is put forward for network optimization, and becomes a research focus.
Routing optimization plays a key role in traffic engineering, finding multiple paths between source-destination pairs, and directing traffic on them. Optimized multi-path routing divides traffic flows flexibly between available paths, making network more efficient and robust. Today's mainstream traffic engineering mechanisms in industry are reviewed; optimal load balancing model for multi-path routing are proposed; without knowledge of traffic matrix, multiple paths seeking and traffic distributing algorithms are proposed in ISP backbone network and data center network separately. The main contributions are as follows.
(1) On the Development of Network Traffic Engineering. Methods employed in today's traffic engineering are put together, and their implementations in IP network are classified for investigating from various aspects. First, public network data for research purposes, topology inclusive, are examined. Second, from an aspect of routing extent, intra-domain and inter-domain traffic engineering mechanisms are introduced; routing algorithms under these topics are also involved. Finally, new aspects are applied to review traffic engineering methods mentioned. Collecting and analyzing existing ones in various ways potentially lead to creative methods. Finally, traffic engineering in data center network is also reviewed.
(2) Minimizing Sum of Path-cost Model and Algorithm for Traffic Balancing. Traffic balancing in routing optimization problem targets to minimize network congestion in traffic engineering. How to select paths for traffic balancing becomes a challenging problem. For minimizing network congestion, the paper argues that network congestion is determined by paths'congestion, and proposes the minimizing sum of path-cost model of traffic balancing. For path selection in routing traffic, a minimal cost path algorithm is proposed. On the basis of real network topology and traffic demand, experiments are conducted to verify the model and algorithm proposed, and results show a nearly20%decrease of maximal link utilization.
(3) Min-Cut Multi-Path Routing Algorithm. Balanced traffic distribution can be archived through traffic engineering, and therefore network congestion is avoided. Today, routing through multiple paths to balance traffic distribution becomes a traffic engineering focus. As enforced by the restrictions of current routing mechanisms, existing multi-path routing algorithms could not get optimal traffic distribution, and therefore could not control network congestion efficiently. On the basis of minimum cut theory, the paper propose a min-cut multi-path (MCMP) routing algorithm, which select key paths of small quantity and distribute traffic evenly among selected paths. MCMP is apt to implement and control congestion at bottleneck links. With real traffic datasets, experiments are carried on European and North American backbone networks. Comparing to OSPF routing algorithm used in intra-domain network and a multiple paths routing algorithm used in optimal model, the maximum link load resulted from MCMP routing algorithm decreases over41%and20%separately.
(4) Big-Flow Collision Avoidance Multi-Path Routing Algorithm in Data Center Network. To accommodate demand's variation and network's scalability, traffic engineering in data center has become an interesting focus in research field. As services supported by data center proliferate in diversity and in extent, big flows herein are popular; however, traditional routing algorithms cannot afford to resolve the collision problem of the flows. The paper propose an collision avoidance algorithm for the problem mentioned; the algorithm finds a path set in advance, primary routes for delivering big flows, and secondary routes for sharing traffic load simultaneously. Experiments carried out in typical data center topology exhibit that the proposed algorithm performs well in reducing maximum link load of core links, as opposed to traditional routing algorithms. Our collision avoidance algorithm is suited for deploying in distributed manner, since its nature of not concerning network status.
引文
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[1]Kandula S, Sengupta S, Greenberg A, et al. The nature of data center traffic: measurements & analysis. In Proceedings of the 9th ACM SIGCOMM conference on Internet measurement conference. ACM,2009:202-208.
[2]Benson T, Anand A, Akella A, et al. Understanding data center traffic characteristics. ACM SIGCOMM Computer Communication Review,40(1),2010: 92-99.
[3]Chen K, Hu C, Zhang X, et al. Survey on routing in data:insights and future directions. Network, IEEE,25(4),2011:6-10.
[4]Lee Y, Mukherjee B. Traffic engineering in next-generation optical networks. Communications Surveys & Tutorials, IEEE,6(3),2004:16-33.
[5]Wang N, Ho K, Pavlou G, et al. An overview of routing optimization for Internet traffic engineering. Communications Surveys & Tutorials, IEEE,10(1),2008: 36-56.
[6]Greenberg A, Hamilton J R, Jain N, et al. VL2:a scalable and flexible data center network. In ACM SIGCOMM Computer Communication Review. ACM,39(4), 2009:51-62.
[7]Benson T, Akella A, Maltz D A. Network traffic characteristics of data in the wild. In Proceedings of the 10th ACM SIGCOMM conference on Internet measurement. ACM,2010:267-280.
[8]Al-Fares M, Loukissas A, Vahdat A. A scalable, commodity data center network architecture. In ACM SIGCOMM Computer Communication Review. ACM, 38(4),2008:63-74.
[9]Niranjan Mysore R, Pamboris A, Farrington N, et al. PortLand:a scalable fault-tolerant layer 2 data center network fabric. In ACM SIGCOMM Computer Communication Review. ACM,39(4),2009:39-50.
[10]Heller B, Seetharaman S, Mahadevan P, et al. ElasticTree:saving energy in data center networks. In Proceedings of the 7th USENIX conference on Networked systems design and implementation.2010:17-17.
[11]Al-Fares M, Radhakrishnan S, Raghavan B, et al. Hedera:Dynamic flow scheduling for data center networks. In Proceedings of the 7th USENIX conference on Networked systems design and implementation.2010:19-19.
[12]Benson T, Anand A, Akella A, et al. The case for fine-grained traffic engineering in data-centers. INM/WREN,10,2010.
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[18]Guo C, Lu G, Li D, et al. BCube:a high performance, server-centric network architecture for modular data. In ACM SIGCOMM Computer Communication Review,39(4),2009:63-74.