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An enhanced QoS CBT multicast routing protocol based on Genetic Algorithm in a hybrid HAP-Satellite system

机译:混合HAP-Satellite系统中基于遗传算法的增强型QoS CBT组播路由协议

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A QoS multicast routing scheme based on Genetic Algorithms (GA) heuristic is presented in" this paper. Our proposal, called Constrained Cost-Bandwidth-Delay Genetic Algorithm (CCBD-GA), is applied to a multilayer hybrid platform that includes High Altitude Platforms (HAPs) and a Satellite platform. This GA scheme has been compared with another GA well-known in the literature called Multi-Objective Genetic Algorithm (MOGA) in order to show the proposed algorithm goodness. In order to test the efficiency of GA schemes on a multicast routing protocol, these GA schemes are inserted into an enhanced version of the Core-Based Tree (CBT) protocol with QoS support. CBT and GA schemes are tested in a multilayer hybrid HAP and Satellite architecture and interesting results have been discovered. The joint bandwidth-delay metrics can be very useful in hybrid platforms such as that considered, because it is possible to take advantage of the single characteristics of the Satellite and HAP segments. The HAP segment offers low propagation delay permitting QoS constraints based on maximum end-to-end delay to be met. The Satellite segment, instead, offers high bandwidth capacity with higher propagation delay. The joint bandwidth-delay metric permits the balancing of the traffic load respecting both QoS constraints. Simulation results have been evaluated in terms of HAP and Satellite utilization, bandwidth, end-to-end delay, fitness function and cost of the GA schemes.
机译:本文中提出了一种基于遗传算法(GA)启发式的QoS组播路由方案。我们的提案(称为约束成本带宽延迟遗传算法(CCBD-GA))被应用于包含高海拔平台的多层混合平台。 (HAP)和Satellite平台,将该GA方案与文献中称为多目标遗传算法(MOGA)的另一种GA进行了比较,以证明该算法的优越性,以测试GA方案的效率在多播路由协议上,将这些GA方案插入具有QoS支持的基于核心树(CBT)协议的增强版本中,并在多层混合HAP和Satellite体系结构中测试了CBT和GA方案,并发现了有趣的结果。联合带宽延迟指标在混合平台(如所考虑的平台)中可能非常有用,因为可以利用卫星和HAP段的单个特性。 HAP段提供了低传播延迟,允许基于要满足的最大端到端延迟来进行QoS约束。相反,卫星部分提供了较高的带宽容量和更高的传播延迟。联合带宽延迟量度允许考虑两个QoS约束来平衡流量负载。已根据HAP和卫星利用率,带宽,端到端延迟,适应度函数和GA方案的成本对仿真结果进行了评估。

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