Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/26708

TitleA framework for robust traffic engineering using evolutionary computation
Author(s)Pereira, Vítor
Rocha, Miguel
Cortez, Paulo
Rio, Miguel
Sousa, Pedro
KeywordsRobust traffic engineering
Optimization
Network resilience
Evolutionary computation
Autonomous configuration
Issue date2013
PublisherSpringer
JournalLecture Notes in Computer Science
Abstract(s)In current network infrastructures, several management tasks often require significant human intervention and can be of high complexity, having to consider several inputs to attain efficient configurations. In this perspective, this work presents an optimization framework able to automatically provide network administrators with efficient and robust routing configurations. The proposed optimization tool resorts to techniques from the field of Evolutionary Computation, where Evolutionary Algorithms (EAs) are used as optimization engines to solve the envisaged NP-hard problems. The devised methods focus on versatile and resilient aware Traffic Engineering (TE) approaches, which are integrated into an autonomous optimization framework able to assist network administrators. Some examples of the supported TE optimization methods are presented, including preventive, reactive and multi-topology solutions, taking advantage of the EAs optimization capabilities.
TypeConference paper
URIhttp://hdl.handle.net/1822/26708
ISBN9783642389979
DOI10.1007/978-3-642-38998-6_1
ISSN0302-9743
Publisher versionhttp://link.springer.com/chapter/10.1007/978-3-642-38998-6_1
Peer-Reviewedyes
AccessRestricted access (UMinho)
Appears in Collections:CAlg - Artigos em livros de atas/Papers in proceedings

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