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A New Flow-Level Load Balance in MPLS Network Based on Distributable Traffic

机译:基于可分配流量的MPLS网络中新的流级负载均衡

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摘要

Load distribution across multiple parallel paths is an important consideration. In many practical contexts, the aggregate traffic from source to sink may be such that no single link can carry the load. In an MPLS domain, this problem can be addressed by instantiating multiple paths. The main objective of this paper balances traffic at the flow level among the parallel Label Switched Paths (LSPs) in MPLS networks. Different from other proposals, our new framework is based on the distributable traffic (DT), where cross-traffic in real networks is considered, and each LSP is modeled as an M/G/l processor-sharing queue. We define a flow to be a sequence of packet having the same identifier, and dispatch packet belonging to one flow to the same path, so the packet disorder problem is avoided effectively. This mechanism only needs to be implemented in the ingress LSRs and the egress LSRs. A new defined cost function is being used to distribute traffic to path. We computer the cost function based on the delay and packet loss of each LSPs, and minimize the cost function. The minimized cost function is inverse ratio to DT. If the cost function of a certain LSP is smaller, it means that more traffic can be distributed on this LSP. Extensive simulations using NS2 are performed with MPLS modules. Simulation results show that our approach so effective that the throughput is increased significantly and reduces the end-to-end delay and the packet drop rate, and it can distribute the traffic onto parallel LSPs more evenly and fairly.
机译:跨多个并行路径的负载分配是重要的考虑因素。在许多实际情况中,从源到接收器的总流量可能使得没有任何一条链路可以承载负载。在MPLS域中,可以通过实例化多个路径来解决此问题。本文的主要目标是在MPLS网络中的并行标签交换路径(LSP)之间的流量级别上平衡流量。与其他提议不同,我们的新框架基于可分配流量(DT),其中考虑了实际网络中的交叉流量,并且每个LSP被建模为M / G / l处理器共享队列。我们将流定义为具有相同标识符的数据包序列,并将属于一个流的数据包调度到同一路径,从而有效避免了数据包混乱问题。此机制仅需要在入口LSR和出口LSR中实现。新定义的成本函数用于将流量分配到路径。我们根据每个LSP的延迟和丢包来计算成本函数,并最小化成本函数。最小成本函数是与DT成反比。如果某个LSP的代价函数较小,则意味着可以在该LSP上分配更多的流量。使用NS2的广泛仿真是通过MPLS模块执行的。仿真结果表明,该方法有效地提高了吞吐量,减少了端到端的延迟和丢包率,并且可以将流量更均匀,更公平地分配到并行LSP上。

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