Load balancing is one of the main goals of Software-Defined Networking (SDN). Distributing the traffic among the possible paths of a network according to specific rules allows SDN systems to increase their global performance index in term of resource usage and scalability. In a previous paper, the authors introduced Adaptive Alienated Ant Algorithm for Software-Defined Networking (A4SDN), a distributed, adaptive, load-balancing algorithm for traffic engineering on SDN showing its ability to optimise the network performance in terms of throughput, communication delay and packet loss rate. In this paper, the authors analyse how the performance of A4SDN are influenced by the underlying topology. For each considered topology, the performance of A4SDN are successfully with those of Extended Dijkstra algorithm. The tests show that the performance of A4SDN are the best when the average number of available shortest paths for each couple of nodes rises.

Evaluating the performance of A4SDN on various network topologies

Cammarata, Giovanni;DI STEFANO, Antonella;Morana, Giovanni;Zito, Daniele
2016-01-01

Abstract

Load balancing is one of the main goals of Software-Defined Networking (SDN). Distributing the traffic among the possible paths of a network according to specific rules allows SDN systems to increase their global performance index in term of resource usage and scalability. In a previous paper, the authors introduced Adaptive Alienated Ant Algorithm for Software-Defined Networking (A4SDN), a distributed, adaptive, load-balancing algorithm for traffic engineering on SDN showing its ability to optimise the network performance in terms of throughput, communication delay and packet loss rate. In this paper, the authors analyse how the performance of A4SDN are influenced by the underlying topology. For each considered topology, the performance of A4SDN are successfully with those of Extended Dijkstra algorithm. The tests show that the performance of A4SDN are the best when the average number of available shortest paths for each couple of nodes rises.
2016
9781509021406
Adaptive alienated ant algorithm for software-defined networking (A4SDN); Alienated ant algorithm (AAA); Ant colony optimization (ACO); Dijkstra; Load balancing; Routing algorithm; Software defined networking (SDN); Traffic engineering; Computer Networks and Communications
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/298389
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