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An ant-based algorithm for distributed routing and wavelength assignment in dynamic optical networks

机译:动态光学网络中基于蚂蚁的分布式路由和波长分配算法

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Future optical communication networks are expected to change radically during the next decade. To meet the demanded bandwidth requirements, more dynamism, scalability and automatism will need to be provided. This will also require addressing issues such as the design of highly distributed control plane systems and their associated algorithms to respond to network changes very rapidly. In this work, we propose the use of an ant colony optimization (ACO) algorithm to solve the intrinsic problem of the routing and wavelength assignment (RWA) on wavelength continuity constraint optical networks. The main advantage of the protocol is its distributed nature, which provides higher survivability to network failures or traffic congestion. The protocol has been applied to a specific type of future optical network based on the optical switching of bursts. It has been evaluated through extensive simulations with very promising results, particularly on highly congested scenarios where the load balancing capabilities of the protocol become especially efficient. Results on a partially meshed network like NSFNET show that the ant-based protocol outperforms other RWA algorithms under test in terms of blocking probability without worsening other metrics such as mean route length.
机译:未来的光通信网络有望在未来十年发生根本性的变化。为了满足所需的带宽要求,将需要提供更多的动态性,可伸缩性和自动性。这也将需要解决诸如高度分散的控制平面系统的设计及其相关算法之类的问题,以非常迅速地响应网络变化。在这项工作中,我们提出使用蚁群优化(ACO)算法来解决波长连续性约束光学网络上的路由和波长分配(RWA)的内在问题。该协议的主要优点是其分布式特性,可为网络故障或流量拥塞提供更高的生存能力。基于突发的光交换,该协议已应用于特定类型的未来光网络。它已通过广泛的仿真进行了评估,并获得了非常可观的结果,尤其是在协议拥塞的负载平衡能力变得特别高效的高度拥挤的情况下。在像NSFNET这样的部分网状网络上的结果表明,在阻止概率方面,基于蚂蚁的协议优于其他受测RWA算法,而不会恶化其他指标,例如平均路由长度。

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