Topology reconfiguration mechanism for traffic engineering in WDM optical network

Optical wavelength division multiplexed (WDM) networks provide an excellent transmission medium for voice and data traffic, streaming media, and high performance and grid computing needs. Rearrangeability is one compelling characteristic of WDM optical networks that allows network operators to rearrange the networks in response to changing traffic demands and element failures to provide improved network performance. Under changing traffic flows and abhorrent network conditions reconfiguration is an ongoing process. Available approaches are not able to handle extreme load conditions, traffic bursts, and element failures and, so far, these approaches cover only limited aspects of the problem of automated reconfiguration. In this work we present an adaptive reconfiguration mechanism for WDM optical networks (ARWON). Two heuristically based algorithms, combination algorithm (CA) and multi lightpath change (MLPC) algorithm, are also proposed to support implementation of ARWON. Simulation experiments covered all ranges of traffic flows and element failure scenario and performance of ARWON was validated with an established contemporary reconfiguration algorithm. Results show that under all loading conditions and link failure scenario ARWON performed better than the comparison algorithm. Under extreme loading conditions ARWON incurred 11 times less traffic loss than single lightpath change (SLPC) algorithm and on average SLPC was carrying 20 more lightpaths than ARWON, per observation cycle, that were 100 percent loaded. Under link failure scenario ARWON recovered faster and rerouted the traffic in one step, whereas SLPC recovered slowly and recovery took much longer duration than ARWON. For other loading conditions, ranging from low to high loading, it was observed that during early stages of simulation ARWON performs at par or marginally better than SLPC. Performance of ARWON steadily improves as simulation progresses over longer duration.