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Quality of Service (QoS) Optimization in a Multicast Routing: A Hybrid Solution

机译:组播路由中的服务质量(QoS)优化:混合解决方案

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Optimizing the QoS of multicast routing with multiple constraints is a NP-hard problem. Thus, the use of approximate methods is unavoidable. This article proposes to modify Bat Algorithm (BA) to solve such problem. BA is a metaheuristic that has been applied to several issues of various fields and has given good results, which has owned him a good reputation in terms of robustness and performance. Like any metaheuristic, BA can be trapped in a local optimum. In order to avoid such problem, the authors propose to hybridize BA with the quantum principle and introduce the chaotic map in the calculation of parameters leading to more diversification. The authors chose to adopt a quantum representation for the solutions. The approach, named quantum Bat Algorithm with Chaotic Map (CBAQEA), was experimented and compared with other well-known methods. The experimental results reveal the efficiency and the superiority of the proposed algorithm in terms of multicast routing cost with a good trade-off between intensification and diversification without premature convergence compared to other algorithms in the literature.
机译:具有多个约束条件的多播路由的QoS优化是一个NP难题。因此,不可避免地要使用近似方法。本文提出修改Bat算法(BA)来解决此问题。 BA是一种元启发式方法,已应用于各个领域的多个问题并取得了良好的效果,在稳健性和性能方面赢得了良好的声誉。像任何元启发式方法一样,BA可以陷入局部最优中。为了避免这种问题,作者提出将BA与量子原理杂交,并在参数计算中引入混沌图谱,从而使分布更加多样化。作者选择采用量子表示法解决方案。实验了该方法,称为带有混沌映射的量子蝙蝠算法(CBAQEA),并将其与其他知名方法进行了比较。实验结果表明,与文献中的其他算法相比,该算法在多播路由成本方面具有较高的效率和优势,并且在强化和多样化之间取得了良好的折衷,并且没有过早收敛。

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