The concept of extended cloud requires efficient network infrastructure to support ecosystems reaching form the edge to the cloud(s). Standard approaches to network load balancing deliver static solutions that are insufficient for the extended clouds, where network loads change often. To address this issue, a genetic algorithm based load optimizer is proposed and implemented. Next, its performance is experimentally evaluated and it is shown that it outperforms other existing solutions.

翻译：扩展云的概念要求高效的网络基础设施，以支持从边缘到云端的生态系统。标准的网络负载均衡方法提供的是静态解决方案，无法满足网络负载频繁变化的扩展云需求。针对这一问题，提出并实现了一种基于遗传算法的负载优化器。随后通过实验评估其性能，结果表明该方案优于现有的其他解决方案。