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Università degli studi di Catania

Bio-inspired routing algorithms for Software Defined Networking

Abstract

dc:description

In recent years, several projects have emerged with the aim of addressing the challenge of providing solutions for the deployment, monitoring, adaptation, and management of clouds belonging to different enterprises/organisations. In addition, the concept of Green Computing and, more specifically, energy-aware solutions have gained attention in the last few years in many fields of ICT: network management is one of those. Today s power consumption is considered a fundamental parameter to take into account when a new routing strategy is designed, just as with latency, bandwidth or error rate. In such scenarios network connectivity is one of the key factors. SDN technologies represent a good solution to face this challenge. By separating the control plane from the data plane, they can give the cloud provider the opportunity to specify both the network topologies and routing schemes on-the fly, guaranteeing, at same time, a specific level of isolation. My work produced an algorithm for traffic engineering on an SDN based on the Alienated Ant Algorithm, a heuristic solution inspired by a non-natural behaviour of ants colonies.

Degree

thesis:*
Grantor dc:publisher
Università degli studi di Catania
Year dc:date
2017

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • CAMMARATA, GIOVANNI
Contributors dc:contributor
  • FORTUNA, LUIGI
  • DI STEFANO, Antonella

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • info:eu-repo/semantics/openAccess
  • license:PUBBLICO - Pubblico con Copyright
  • license uri:iris.PUB02
Language dc:language
ita

Identifiers

dc:identifier.*
OAI identifier oai:identifier
oai:www.iris.unict.it:20.500.11769/583554

Chain of custody

source
Harvested from
Università degli Studi di Catania
Base URL
www.iris.unict.it/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

CAMMARATA, GIOVANNI. Bio-inspired routing algorithms for Software Defined Networking. Università degli studi di Catania, 2017. https://hdl.handle.net/20.500.11769/583554