This thesis investigates methods to enhance the robustness of KPN's network. As reliance on telecom networks grows, improving network resilience is paramount. Two primary strategies exist: minimizing failure occurrence and mitigating failure impact. This research focuses on the latter, specifically increasing network redundancy by transforming existing ring structures into strand structures.

Current ring structures in the network avoid single points of failure (SPOFs) at the link level but fail to address node-level SPOFs, particularly at Metro Core (MC) locations. MC locations are pivotal, as they manage customer sessions and route all household network traffic. Node failures at these locations can disrupt connections for up to 100,000 households. Thus, ensuring that a single node-level failure can be compensated by another node is crucial. This requires considering both equipment and building failures, with geographically distant backup nodes necessary for the latter.

Transforming rings into strands, which inherently include two geographically separated MC locations, addresses these issues but incurs significant costs. While an exact cost estimation is beyond the scope of this research, the study approximates the length of additional cables required, totaling 206 kilometers. Including cost multipliers for tunnels, bridges, and highways, the adjusted length is equivalent to 222 'kilometers' of cable. Despite the substantial cost, node failures at the equipment level, which are more common, can be mitigated with redundant equipment at MC locations. Therefore, a cost-effective alternative might be forming strands only where rings from different access areas are already in proximity.

Almende B.V., a technologically innovative and research-oriented company, has been working on a new algorithm that optimizes routes for parcel delivery trucks. The algorithm contains novel features, like including the possible use of autonomous vehicles, that are at this moment in time not taken into account in existing route optimization algorithms and thus visualization applications. To this end and to get a more tangible overview of the algorithm’s behavior and performance, they requested to have a customized visualization tool developed. This report describes the process and results of developing such a tool. The tool is presented as a single-page application and has been partly depicted on the cover of this document. The goal of the project is to have a more clear overview of the routing algorithm’s capabilities, by showing its unique features on a map and displaying statistics on the side. In addition, comparing the algorithm to existing ones should provide added insights into the (expected) benefits of the new algorithm. The main purpose of the tool developed in this project is to show insight into the workings of the algorithm and to help with enhancing and developing the algorithm. An added side-bonus is that the tool can also be used to show the performance to various groups of interested parties.