Information and communication technology (ICT) is one of the sectors that have the highest energy consumption worldwide. It implies that the use of energy in the ICT must be controlled. A software-defined network (SDN) is a new technology in computer networking. It separates the control and data planes to make networks more programmable and flexible. To obtain maximum scalability and robustness, load balancing is essential. The SDN controller has full knowledge of the network. It can perform load balancing efficiently. Link congestion causes some problems such as long transmission delay and increased queueing time. To overcome this obstacle, the link load balancing strategy is useful. The link load-balancing problem has the nature of NP-complete; therefore, it can be solved using a meta-heuristic approach. In this study, a novel energy-aware dynamic routing method is proposed to solve the link load-balancing problem while reducing power consumption using the multi-objective artificial bee colony algorithm and genetic operators. The simulation results have shown that the proposed scheme has improved packet loss rate, round trip time and jitter metrics compared with the basic ant colony, genetic-ant colony optimisation, and round-robin methods. Moreover, it has reduced energy consumption.

中文翻译：

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基于多目标人工蜂群算法和遗传算子的软件网络能量感知动态链路负载均衡方法

信息和通信技术（ICT）是全球能耗最高的行业之一。这意味着必须控制ICT中的能源使用。软件定义网络（SDN）是计算机网络中的一项新技术。它将控制平面和数据平面分开，以使网络更具可编程性和灵活性。为了获得最大的可伸缩性和鲁棒性，负载平衡至关重要。SDN控制器完全了解网络。它可以有效地执行负载平衡。链路拥塞会导致一些问题，例如较长的传输延迟和增加的排队时间。为克服此障碍，链接负载平衡策略很有用。链路负载均衡问题具有NP完全的性质。因此，可以使用元启发式方法来解决。在这个研究中，提出了一种新的能量感知动态路由方法，该方法利用多目标人工蜂群算法和遗传算子在解决链路负载均衡问题的同时降低功耗。仿真结果表明，与基本蚁群，遗传蚁群优化和轮询方法相比，该方案具有更好的丢包率，往返时间和抖动指标。此外，它降低了能耗。和循环法。此外，它降低了能耗。和循环法。此外，它降低了能耗。