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Energy-Efficient Next-Generation Passive Optical Networks Based on Sleep Mode and Heuristic Optimization

机译:基于睡眠模式和启发式优化的高能效下一代无源光网络

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In this article, an energy-efficiency mechanism for next-generation passive optical networks is investigated through heuristic particle swarm optimization. Ten-gigabit Ethernet-wavelength division multiplexing optical code division multiplexing-passive optical network next-generation passive optical networks are based on the use of a legacy 10-gigabit Ethernet-passive optical network with the advantage of using only an en/decoder pair of optical code division multiplexing technology, thus eliminating the en/decoder at each optical network unit. The proposed joint mechanism is based on the sleep-mode power-saving scheme for a 10-gigabit Ethernet-passive optical network, combined with a power control procedure aiming to adjust the transmitted power of the active optical network units while maximizing the overall energy-efficiency network. The particle swarm optimization based power control algorithm establishes the optimal transmitted power in each optical network unit according to the network pre-defined quality of service requirements. The objective is controlling the power consumption of the optical network unit according to the traffic demand by adjusting its transmitter power in an attempt to maximize the number of transmitted bits with minimum energy consumption, achieving maximal system energy efficiency. Numerical results have revealed that it is possible to save 75% of energy consumption with the proposed particle swarm optimization based sleep-mode energy-efficiency mechanism compared to 55% energy savings when just a sleeping-mode-based mechanism is deployed.
机译:本文通过启发式粒子群算法研究了下一代无源光网络的能量效率机制。十吉比特以太网波分复用光码分多路复用无源光网络下一代无源光网络基于对传统的十吉比特以太网无源光网络的使用,其优点是仅使用一对编码器/解码器对。光码分复用技术,从而消除了每个光网络单元的编码器/解码器。拟议的联合机制基于10 Gb以太网无源光网络的睡眠模式节能方案,并结合了旨在调整有源光网络单元的传输功率,同时最大程度地提高整体能量利用率的功率控制程序。效率网络。基于粒子群优化的功率控制算法根据网络预定义的服务质量要求,在每个光网络单元中建立最佳传输功率。目的是通过调整其发射器功率来根据业务需求控制光网络单元的功率消耗,从而尝试以最小的能量消耗来最大化发送比特的数量,从而实现最大的系统能量效率。数值结果表明,与仅部署基于睡眠模式的机制相比,使用基于粒子群优化的睡眠模式能效机制可以节省75%的能耗。

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