Performance analysis of genetic algorithm (GA)-based multi-constrained path routing algorithm

Abstract

To support networked multimedia applications, it is important for the network to provide guaranteed quality-of-service (QoS). One way to provide such services is for the network to perform QoS routing, where the path taken must fulfill a given set of constraints. Multi-constrained path (MCP) problem refers to the problem of finding a path through a network subject to multiple additive constraints. It has been proven that this problem is Non-deterministic Polynomial time (NP)-complete and therefore no exact algorithm can be found. As such, various heuristics and approximation algorithms have been proposed to solve the MCP problem. This paper proposed a solution to the MCP problem using genetic algorithm (GA). The effectiveness of the proposed algorithm is evaluated through simulation. The performance of the algorithm is then compared with an exact algorithm called the depth first search and a common shortest path algorithm called the Dijkstra’s algorithm. The result of the simulation shows that the performance of the proposed algorithm is almost comparable to an exact algorithm, while at the same time can execute much faster. The proposed algorithm has also been shown to have good network link utilization and is able to scale well with network size. Key words: Genetic algorithm, multi-constrained path problem, quality-of-service (QoS), routing.