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:扩展云概念需要高效的网络基础架构来支持从边缘到云端的生态系统。标准的网络负载平衡方法提供的是静态解决方案,对于经常变化的网络负载,在扩展云中显得不够充分。为了解决这个问题,提出并实现了基于遗传算法的负载优化器,并通过实验评估其性能,表明其优于目前其他现有解决方案。