Optical burst switching (OBS) - a new paradigm for an optical Internet
Journal of High Speed Networks - Special issue on optical networking
Algorithms for burst rescheduling in WDM optical burst switching networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Fault Management with Fast Restoration for Optical Burst Switched Networks
BROADNETS '04 Proceedings of the First International Conference on Broadband Networks
Dynamic load balancing in IP-over-WDM optical burst switching networks
Computer Networks: The International Journal of Computer and Telecommunications Networking
Load balancing routing with bandwidth-delay guarantees
IEEE Communications Magazine
Control architecture in optical burst-switched WDM networks
IEEE Journal on Selected Areas in Communications
IEEE Journal on Selected Areas in Communications
Wide-area Internet traffic patterns and characteristics
IEEE Network: The Magazine of Global Internetworking
Blocking probability evaluation of end-to-end dynamic WDM networks
Photonic Network Communications
Wavelength converter allocation considering the streamline effect in OBS networks
Computer Communications
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Route optimization in optical burst switching (OBS) networks is investigated in this paper. Two route optimization problems are studied. The first problem considers the network in the normal working state where all the links are working properly. The route for each flow is decided so as to minimize the overall network burst loss. The second problem considers the failure states apart from the normal working state. The primary and backup paths for each flow are determined in such a way to minimize the expected burst loss over the normal and failure states. We argue that route selection based on load balancing or the traditional Erlang B formula is not efficient because of an important feature called the streamline effect. We analyze the streamline effect and propose a more accurate loss estimation formula which considers the streamline effect. Based on this formula, we develop mixed integer linear programming (MILP) formulations for the two problems. Since the MILP-based solutions are computationally intensive, we develop heuristic algorithms. We verify the effectiveness of our algorithms through numerical results obtained by solving the MILP formulations with CPLEX and also through simulation results.