DocumentCode :
654141
Title :
Improving network migration optimization utilizing memetic algorithms
Author :
Turk, Sener ; Hao Liu ; Radeke, Rico ; Lehnert, Ralf
Author_Institution :
Commun. Lab., Tech. Univ. Dresden, Dresden, Germany
fYear :
2013
fDate :
28-31 Oct. 2013
Firstpage :
1
Lastpage :
8
Abstract :
In this paper we describe the basics of the network migration problem, as well as the solution of the problem using meta heuristics. The class of heuristics described and applied in this paper is called memetic algorithms. Those are explained and results regarding network migration are presented. To evaluate potential algorithm candidates a generic TSP has been implemented and tested. The mapping of the network migration problem to memetic algorithms and to the algorithm library GALib is explained as well. Our main goal is the optimization of network migration costs, by respecting increasing demands over the migration period, while device costs per bit are decreasing. The mapping of the specified problem to the heuristic variants is also of major interest.
Keywords :
genetic algorithms; local area networks; TSP; algorithm library GALib; memetic algorithm; meta heuristics; network migration optimization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Global Information Infrastructure Symposium, 2013
Conference_Location :
Trento
Type :
conf
DOI :
10.1109/GIIS.2013.6684345
Filename :
6684345
Link To Document :
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