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Ant Based Multicast Routing Algorithm with Multiple Constraints for Mobile Adhoc Networks

机译:基于蚁群组播路由算法,具有多种移动adhoc网络的约束

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One particular challenging environment for multicast is a mobile ad-hoc network (MANET). Existing studies show that tree-based and mesh based on-demand protocols are not necessarily the best choice, since associated overhead will be more. Several algorithms based on the Ant Colony Optimization (ACO) approach minimizes the cost of the tree under multiple constraints. These algorithms treat the Traffic Engineering Multicast problem as a single-purpose problem with several constraints. The main disadvantage of this approach is the necessity of a predefined upper bound that can exclude good trees from the final solution. This paper presents a design on Ant-Colony Based Multicast Routing (AMR) algorithm for MANETs, to solve the Traffic Engineering Multicast problem that optimizes several objectives simultaneously. The algorithm calculates one more additional constraint in the cost metric, which is the product of average-delay and the maximum depth of the multicast tree and try to minimize this combined cost metric. Simulation results show that the proposed algorithm outperforms all previous algorithms by forming the multicast tree with varying sizes.
机译:多播的一个特殊具有挑战性的环境是移动临时网络(MANET)。现有研究表明,基于树的基于格式的基于网状的按需协议不一定是最佳选择,因为相关的开销将更多。基于蚁群优化(ACO)方法的几种算法最小化了多个约束下树的成本。这些算法将流量工程组播问题视为具有多个约束的单一目的问题。这种方法的主要缺点是必须从最终解决方案中排除良好树木的预定义上限的必要性。本文介绍了基于野蛮的蚁群组播路由(AMR)算法的设计,解决了同时优化了多个目标的流量工程组播问题。该算法在成本度量中计算一个额外的约束,这是平均延迟和多播树的最大深度的乘积,并尝试最小化该成本度量。仿真结果表明,该算法通过形成具有不同大小的组播树来优于所有先前的算法。

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