Date of Award
traffic grooming techniques
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Recent research has clearly established that holding-time-aware routing and wavelength assignment (RWA) schemes lead to significant improvements in resource utilization for scheduled traffic. By exploiting the knowledge of the demand holding times, this thesis proposes new traffic grooming techniques to achieve more efficient resource utilization with the goal of minimizing resources such as bandwidth, wavelength channels, transceivers, and energy consumption. This thesis also introduces a new model, the segmented sliding window model, where a demand may be decomposed into two or more components and each component can be sent separately. This technique is suitable for applications where continuous data transmission is not strictly required such as large file transfers for grid computing. Integer linear program (ILP) formulations and an efficient heuristic are put forward for resource allocation under the proposed segmented sliding window model. It is shown that the proposed model can lead to significantly higher throughput, even over existing holding-time-aware models.
Chen, Ying, "Resource Allocation for Periodic Traffic Demands in WDM Networks" (2013). Electronic Theses and Dissertations. 4918.