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An Optimized Ant Colony Algorithm Based On The Gradual Changing Orientation Factor For Multi-constraint Qos Routing

机译:基于渐变方向因子的多约束Qos路由优化蚁群算法

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摘要

The ad hoc network has been attracting increasing attention of researchers owing to its good performance and special application. The search of route that satisfies such multi-constraints as delay, jitter and bandwidth in ad hoc network can facilitate the solution to multi-media transmission. The problem of multi-constraint is generally an NP-Hard problem. This paper deals with the problem by adding an orientation heuristic factor to the conventional ant colony algorithm, which enables the ant to get rid of the blindness at the initial stage of path searching. The ant in the modified algorithm not only makes use of the previous search findings, but also reduces the misguiding effect of pheromones on the irrelevant paths, thus overcoming the problem of slow convergence. The choice and the extent of the effect of the orientation heuristic factor in the modified algorithm is our focus, and the gradual changing orientation factors is also studied. The gradual changing orientation factor not only enables the ant to take advantage of direction to assist path search, but also adjust convergence speed and exactitude. Simulation results indicate that the modified algorithm can quickly find the feasible solution to the network routing problem. The method adopted can help find better solutions in shorter time.
机译:自组织网络由于其良好的性能和特殊的应用而引起了越来越多的研究者的关注。在ad hoc网络中搜索满足诸如延迟,抖动和带宽等多重约束的路由可以简化多媒体传输的解决方案。多约束问题通常是NP-Hard问题。针对这种问题,在传统的蚁群算法中增加了一种定向启发式因子,使蚂蚁摆脱了路径搜索初期的盲目性。改进算法中的蚂蚁不仅利用了先前的搜索结果,还减少了信息素对不相关路径的误导作用,从而克服了收敛速度慢的问题。方向启发式因子在改进算法中影响的选择和程度是我们的研究重点,并且研究了逐步变化的方向因子。逐渐变化的定向因子不仅使蚂蚁能够利用方向来辅助路径搜索,而且还可以调整收敛速度和精确度。仿真结果表明,改进算法可以快速找到解决网络路由问题的可行方案。采用的方法可以帮助您在较短的时间内找到更好的解决方案。

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