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A Survey of Ant Colony Optimization Algorithms for Telecommunication Networks

机译:电信网络蚁群优化算法研究

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Optical and ad-hoc networks which fulfill the communications requirements of complex applications must meet the Quality of Service (QoS) demanded by these applications, such as transmission delay. These demands are hard to satisfy in the presence of unpredictable behavior in the environment such as interference, traffic congestion, etc. Algorithms based on Ant Colony Optimization (ACO) offer an effective approach to meet such challenges since they are well suited to the dynamic routing optimization and dynamic resource reassignment required by these applications. In this paper, the author presents a survey of Ant Colony Optimization variants applied to ad-hoc and optical networks. The ACO variant called AntHocNet in particular will be reviewed, analyzed, and criticized from the point of view of emergent applications for environment management such as Intelligent Transportation Systems (ITS).
机译:满足复杂应用程序通信要求的光学和自组织网络必须满足这些应用程序所要求的服务质量(QoS),例如传输延迟。在环境中存在不可预测的行为(例如干扰,交通拥塞等)的情况下,很难满足这些要求。基于蚁群优化(ACO)的算法提供了一种有效的方法来应对此类挑战,因为它们非常适合动态路由这些应用程序需要优化和动态资源重新分配。在本文中,作者提出了适用于自组织网络和光网络的蚁群优化变量的调查。 ACO变体AntHocNet尤其将从智能交通系统(ITS)等新兴的环境管理应用程序的角度进行审查,分析和批评。

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