Heuristic constraint-path routing decision system

W. Goodridge, W. Robertson, W. Phillips, S. Sivakumar
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引用次数: 13

Abstract

Heuristic QoS algorithms under strict constraints perform poorly in terms of finding a path that is suitable for a user's QoS needs-the multiple constraint path problem (MCP). Exact QoS algorithms, on the other hand, guarantee that a path satisfying user needs would be found and offer a more realistic approach for solving the MCP problem in view of the fact that the NP-complete character of graphs are not common in real networks. This fact has driven approaches like the SAMCRA and A*prune algorithms. However, these algorithms still have very high running times relative to heuristic approaches. When QoS routing algorithms are used in online traffic engineering (TE) environments it may be necessary to route thousands of traffic flows each minute. Exact algorithms simply cannot work in such environments. We propose a heuristic algorithm that is suitable for working in an online TE environment. Simulations show that this algorithm produce high success rates in terms of finding suitable constraint paths for user flows while at the same time having execution times comparable to another heuristic based algorithms.
启发式约束路径路由决策系统
在严格约束下的启发式QoS算法在寻找适合用户QoS需求的路径方面表现不佳,即多约束路径问题(MCP)。另一方面,精确的QoS算法保证了找到满足用户需求的路径,并且鉴于图的np完全特征在实际网络中并不常见,为解决MCP问题提供了一种更现实的方法。这一事实推动了SAMCRA和A*修剪算法等方法的发展。然而,与启发式方法相比,这些算法的运行时间仍然非常高。在在线流量工程(TE)环境中使用QoS路由算法时,可能需要每分钟路由数千个流量。精确的算法根本无法在这样的环境中工作。我们提出了一种适合在线TE环境的启发式算法。仿真表明,该算法在为用户流找到合适的约束路径方面产生了很高的成功率,同时与另一种基于启发式算法的执行时间相当。
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