Network flows: theory, algorithms, and applications
Network flows: theory, algorithms, and applications
Analysis of shortest-path routing algorithms in a dynamic network environment
ACM SIGCOMM Computer Communication Review
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Traffic engineering with traditional IP routing protocols
IEEE Communications Magazine
Optimizing OSPF/IS-IS weights in a changing world
IEEE Journal on Selected Areas in Communications
HPSR'09 Proceedings of the 15th international conference on High Performance Switching and Routing
An improved multiple objectives optimization of QoS routing algorithm base on genetic algorithm
WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
EA'09 Proceedings of the 9th international conference on Artificial evolution
Quantifying violations of destination-based forwarding on the internet
Proceedings of the 2012 ACM conference on Internet measurement conference
Achieving high robustness and performance in QoS-aware route planning for IPTV networks
Information Sciences: an International Journal
| Hi-index | 0.00 |
Routing optimization provides network operators with a powerful method for traffic engineering. Its general objective is to distribute traffic flows evenly across available network resources in order to avoid network congestion and quality of service degradation. In this paper we consider routing optimization based on conventional routing protocols where packets are forwarded hop-by-hop in a destination-based manner. Unlike other work in this area, we consider routing protocols, which are able to take into account concave routing metrics in addition to additive ones. The concave link metric introduces an additional degree of freedom for routing optimization, thus, increasing its optimization potential. We present and evaluate a mixed-integer programming model, which works on these metrics. This model unifies the optimization for single-metric and dual-metric routing concepts and also includes the consideration of multipath routing. Furthermore, we propose a heuristic algorithm usable for larger network instances. Numerical results indicate that employment of both the dual-metric concept and multipath routing can achieve considerably better utilization results than default-configured single-metric routing. A significant finding is that metric-based routing optimization with two link metrics often comes close to the results obtainable by optimization of arbitrarily configurable routing.