Quality of Service constrained routing optimization using Evolutionary Computation

Authors:
Miguel Rocha;Pedro Sousa;Paulo Cortez;Miguel Rio
Affiliations:
Center of Computer Science and Technology, CCTC, University of Minho, Campus Gualtar, 4710-057 Braga, Portugal;Center of Computer Science and Technology, CCTC, University of Minho, Campus Gualtar, 4710-057 Braga, Portugal;Department of Information Systems/Algoritmi Center, University of Minho, Campus Azurem, 4800-058 Guimarães, Portugal;Department of Electronic and Electrical Engineering, University College London, Torrington Place, WC1E 7JE London, UK
Venue:
Applied Soft Computing
Year:
2011

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Abstract

In this work, a novel optimization framework is proposed that allows the improvement of Quality of Service levels in TCP/IP based networks, by configuring the routing weights of link-state protocols such as OSPF. Since this is a NP-hard problem, some algorithms from Evolutionary Computation were considered, working over a mathematical model that allows the definition of flexible cost functions that can take into account several measures of the network behaviour, such as network congestion and end-to-end delays. A number of experiments were performed, over a large set of network topologies, where Evolutionary Algorithms (EAs), Differential Evolution, local search methods and common heuristics were compared. EAs make the most promising alternative leading to solutions with an effective network performance, even under unfavourable scenarios. A number of state of the art multi-objective optimization algorithms were also tested, but the proposed EAs still hold as the most consistent method for network optimization.