An Efficient Algorithm for Global Path Optimization in MPLS Networks

This paper proposes an algorithm to solve the optimization of label switched paths (LSPs) in multiprotocol label switching (MPLS) networks. The underlying optimization problem in this task is the well-known unsplittable multicommodity flow problem equipped with practically relevant objective functions and specialized with hard technical requirements.The proposed heuristic algorithm is based on network flow theory. It incorporates iterative shortest path search and performs adaptive edge weight adjustments in order to successfully satisfy all the required traffic demands and to maximize user-defined objectives. The robust algorithm facilitates the incorporation of several strategic and optimization objectives and the fulfillment of certain hard technical requirements of the target problem domain as well. Novel features of the approach include a new adaptive path allocation/deallocation strategy based on the identification of bottleneck links, demand ordering and preprocessing phases, and a systematic path allocation control method.The efficiency of the method is empirically shown on randomly generated networks with practical sizes and topologies, and on a real-world IP (Internet Protocol) backbone network. The algorithm is able to successfully solve difficult problem instances comprising very large instances with 1000 nodes, 3500 edges and 999000 traffic demands. The computational tests demonstrate that the proposed approach can be efficiently applied to solve problem instances that embed MPLS specific hard technical requirements. Furthermore, it is shown that our algorithm offers significantly better performance than the straightforward adaptations of existing methods that were developed for related network optimization problems. Namely, our algorithm produces acceptable results quicker, it can solve problems that were not previously solvable, and it yields better results than the alternative methods. The extensive empirical tests demonstrate the combinatorial properties of the target problem and the performance aspects of the algorithm and its components as well.     

Responsive on-line gateway load-balancing for wireless mesh networks

We propose an adaptive online load-balancing protocol for multi-gateway Wireless Mesh Networks (WMNs) which, based on the current network conditions, balances load between gateways. Traffic is balanced at the TCP flow level and, as a result, the aggregate throughput, average flow throughput and fairness of flows improves. The proposed scheme (referred to as Gateway Load-Balancing, GWLB) is highly responsive, thanks to fast gateway selection and the fact that current traffic conditions are maintained up-to-date at all times without any overhead. It also effectively takes into account intra-flow and inter-flow interference when switching flows between gateway domains. We have found the performance achievable by routes used after gateway selection to be very close to the performance of optimal routes found by solving a MINLP formulation under the protocol model of interference. Through simulations, we analyze performance and compare with a number of proposed strategies, showing that GWLB outperforms them. In particular, we have observed average flow throughput gains of 128% over the nearest gateway strategy.     

Two-terminal routing games with unknown active players

We analyze 2-terminal routing games with linear cost functions and with unknown number of active players. We deal with both splittable and unsplittable models. We prove the existence and uniqueness of a symmetric safety-level equilibrium in such games and show that in many cases every player benefits from the common ignorance about the number of players. Furthermore, we prove new theorems on existence and uniqueness of equilibrium in 2-terminal convex routing games with complete information.