  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.
