Flow-Aware Multi-Topology Adaptive Routing (FAMTAR) is a new approach to multipath and adaptive routing in IP networks which enables automatic use of alternative paths when the primary one becomes congested. It provides more efficient network resource utilization and higher quality of transmission compared to standard IP routing. However, thus far it has only been evaluated through simulations. In this paper we share our experiences from building a real-time FAMTAR router and present results of its tests in a physical network. The results are in line with those obtained previously through simulations and they open the way to implementation of a production grade FAMTAR router.
There are numerous approaches to providing multipath transmissions in IP networks. Multipath solutions can also operate at different layers. The most visible solutions were surveyed in @cite_1 .
@cite_1
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IP networks were designed to provide general connectivity. At their advent, routing methods focused only on finding one optimal path between given endpoints. Although many solutions to sending traffic via multiple paths have appeared over time, the majority of current IP networks are still managed to support only single-path transmissions. This survey examines various approaches which can provide multipath transmissions in existing IP networks. Firstly, the most recognizable solutions are presented, and later, less well-known proposals are introduced. We show how it is possible to realize multipath transmission in source and hop-by-hop routing, multi-topology routing, bio-inspired routing solutions, Valiant's routing, Multi-Protocol Label Switching, Software-Defined Networks, Flow-Aware Multi-Topology Adaptive Routing, Shortest-Path Bridging, Transparent Interconnection of Lots of Links, network virtualization, and Multipath TCP. Moreover, the mentioned approaches are compared, contrasted and subjectively assessed. The goal of the survey is to show that multipath transmissions can be achieved in the current IP networks and in many different ways.