| Description |
Due to network failure, underprovisioning, or temporary unanticipated increases in traffic, networks may become overloaded. In such situations, it may be desirable to prioritize some traffic flows over others, such as for public safety applications or priority customers. Solutions such as priority queuing and differentiated services provide partial answers to that goal, but leave other problems unsolved. The work presents a novel solution using Segment Routing and a Genetic Algorithm optimizer to minimize the impact of network overload on critical traffic flows. The results show that these methods are able to reroute flows using a single midpoint such that the total network overload is less than traditional shortest-path routing while avoiding unnecessarily long paths and taking priority of flows into account. |
