Network migration optimization using meta-heuristics

Traffic demand of backbone networks will increase rapidly in the next years, while equipment costs per bit are shrinking. To cope with this development a technology change toward modern architectures is proposed in literature. This migration process should be financially optimized or improved in terms of energy consumption. Different multi-period optimization approaches are known from literature, while we investigate an all-period network migration optimization using meta-heuristics. This paper comprehends our earlier works using harmony search, particle swarm optimization or genetic algorithms to solve the problem. The target is to deliver detailed plans for the network provider when which network device has to be placed at a certain network node. Therefore economic cost distributions are provided for the planned migration period. Also the performance of the mapped heuristics is of high relevance. (C) 2014 Elsevier GmbH. All rights reserved.