"FMap: Optimizing Network Performance with Fuzzy Map Scheduling"

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The publication "FMap: A fuzzy map for scheduling elephant flows through jumping traveling salesman problem variant toward software-defined networking-based data center networks" presents a comprehensive and innovative approach to addressing the challenges of scheduling elephant flows (EFs) in data center networks (DCNs). The document introduces the FMap approach, which leverages fuzzy inference, a customized weighted traveling salesman problem (WTSP) model, and a genetic algorithm to optimize EF scheduling. The publication addresses the need for a more comprehensive solution that integrates flow prioritization, routing decisions, and fine-grained flow specifics to prevent congestion and degradation of DCN performance. It also discusses the limitations of existing methods and emphasizes the importance of considering flow prioritization and routing decisions under the event of parallel incoming flows. The document highlights the significance of size-aware traffic engineering (TE) in DCNs and the potential impact of EFs on network performance. It also presents the proposed FMap approach as a sophisticated solution to EF scheduling in DCNs, aiming to improve network performance, reduce congestion, and address the challenges associated with handling EFs. In summary, the publication provides valuable insights into the complexities of EF scheduling in DCNs and presents a well-structured and comprehensive approach to addressing these challenges, with the potential to significantly improve the performance and efficiency of data center networks.

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