With the increasing demand for high-quality internet services, deploying GPON/Fiber-to-the-Home networks is one of the biggest challenges that internet providers have to deal with due to the significant investments involved. Automated network design usage becomes more critical to aid with planning the network by minimising the costs of planning and deployment. The main objective is to tackle this problem of optimisation of networks that requires taking into account multiple factors such as the equipment placement and their configuration, the optimisation of the cable routes, the optimisation of the clients' allocation and other constraints involved in the minimisation problem. An AI-based solution is proposed to automate network design, which is a task typically done manually by teams of engineers. It is a difficult task requiring significant time to complete manually. To alleviate this tiresome task, we proposed a Genetic Algorithm using a two-level representation to design the networks automatically. To validate the approach, we compare the quality of the generated solutions with the handmade design ones that are deployed in the real world. The results show that our method can save costs and time in finding suitable and better solutions than existing ones, indicating its potential as a support design tool of solutions for GPON/Fiber-to-the-Home networks. In concrete, in the two scenarios where we validate our proposal, our approach can cut costs by 31% and by 52.2%, respectively, when compared with existing handmade ones, showcasing and validating the potential of the proposed approach.
翻译:随着对高质量互联网服务的需求不断增加,部署GPON / FTTH网络是因涉及重大投资而面临的最大挑战之一。自动网络设计使用变得越来越关键,以帮助规划网络,通过最小化规划和部署成本来实现。其主要目标是解决网络优化问题,需要考虑多个因素,例如设备的放置和配置、电缆路线的优化、客户分配的优化以及涉及最小化问题的其他约束。提出了一种基于人工智能解决方案,自动化网络设计,这是一个通常由工程团队手动完成的任务。这是一项困难的任务,需要大量时间才能手工完成。为了减轻这项繁琐的任务,我们提出了一种使用两级表示的遗传算法自动设计网络。为了验证该方法,我们将生成的解的质量与在现实世界中部署的手工制作的设计进行了比较。结果表明,我们的方法可以节省成本和时间,找到比现有解决方案更适合和更好的解决方案,表明其作为GPON / FTTH网络解决方案的支持设计工具的潜力。具体而言,在我们验证提案的两个情景中,与现有的手工制作方案相比,我们的方法可以分别减少31%和52.2%的成本,展示并验证了所提出的方法的潜力。