AntHocNet: an adaptive nature-inspired algorithm for routing in mobile ad hoc networks
AntHocNet: an adaptive nature-inspired algorithm for routing in mobile ad hoc networks
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DOI：
10.1002/ett.1062
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发表时间：
2005-09-01
影响因子：
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通讯作者：
Gambardella, LM
中科院分区：
文献类型：
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作者：
Di Caro, G;Ducatelle, F;Gambardella, LM
在本文中，我们描述了AntHocNet，路由算法在移动的ad hoc网络。它是一种混合算法，结合了被动式路径建立和主动式路径探测、维护和改进。该算法是基于自然启发的蚁群优化框架。路径学习引导蒙特卡洛抽样使用蚂蚁一样的代理商在一个stigmergic方式进行通信。在一组广泛的模拟实验中，我们比较了AntHocNet与AODV，在该领域的参考算法。我们表明，我们的算法可以优于AODV在不同的评价标准。AntHocNet的性能优势在各种可能的网络场景中都是显而易见的，并且在更大、更稀疏和更移动的网络中会增加。版权所有（c）2005 AEIT。
In this paper, we describe AntHocNet, an algorithm for routing in mobile ad hoc networks. It is a hybrid algorithm, which combines reactive path setup with proactive path probing, maintenance and improvement. The algorithm is based on the nature-inspired ant colony optimisation framework. Paths are learned by guided Monte Carlo sampling using ant-like agents communicating in a stigmergic way. In an extensive set of simulation experiments, we compare AntHocNet with AODV, a reference algorithm in the field. We show that our algorithm can outperform AODV on different evaluation criteria. AntHocNet's performance advantage is visible over a broad range of possible network scenarios, and increases for larger, sparser and more mobile networks. Copyright (c) 2005 AEIT.