►狂賀!!本系陳仁暉教授物聯網研究刊登於IEEE Internet of Things頂尖期刊(SCI, IF: 10.238, Rank: 9/164 (5.49% (Q1)))，獲得TACC學會2022年度最佳期刊論文獎，全體師生祝賀!!

Muhammad Ibrar, Lei Wang*, Gabriel-Miro Muntean, Jenhui Chen*, Nadir Shah, and Aamir Akbar, "IHSF: An Intelligent Solution for Improved Performance of Reliable and Time-sensitive Flows in Hybrid SDN-based FC IoT Systems," IEEE Internet of Things Journal, vol. 8, no. 5, pp. 3130-3142, March 2021. (SCI, IF: 10.238, Rank: 9/164 (5.49% (Q1), 2021) in Computer Science, Information Systems) DOI: 10.1109/JIOT.2020.3024560
2022 Best Journal Paper Award, TACC

The integration of software-defined networking (SDN) into legacy networks causes both operational and deployment issues. In this context, this article proposes a novel approach, called An Intelligent Solution for Improved Performance of Reliable and Time-sensitive Flows in hybrid SDN-based fog computing IoT systems (IHSF). The proposed IHSF approach has three solutions: 1) a novel algorithm to deploy SDN switches between legacy switches to improve network observability; 2) a K -nearest neighbor regression algorithm to predict in real time the reliability of legacy links at the SDN controller based on historic data; this enables the SDN controller to make timely decisions, improving system performance; and 3) a reliable and time-sensitive deep deterministic policy gradient algorithm (RT-DDPG), which optimally computes forwarding paths in hybrid SDN-F for time-critical traffic flows generated by IoT applications. The simulation results show that our proposed IHSF solution has a better performance than the existing approach in terms of network observability time, number of disturbed flows, end-to-end delay, and packet delivery ratio.

將軟體定義網路 (SDN) 整合到傳統網路中會導致營運和部署問題。在此背景下，本文提出了一種新穎的方法，稱為「提高基於 SDN 的混合霧運算物聯網系統 (IHSF) 中可靠且時間敏感流性能的智慧解決方案」。所提出的 IHSF 方法有三種解決方案：1）一種在傳統交換器之間部署 SDN 交換器的新穎演算法，以提高網路可觀測性；2）一個K- 最近鄰迴歸演算法，根據歷史資料即時預測 SDN 控制器上遺留連結的可靠性；這使得SDN控制器能夠及時做出決策，提高系統效能；3) 可靠且時間敏感的深度確定性策略梯度演算法 (RT-DDPG)，可針對物聯網應用產生的時間關鍵型流量最佳化計算混合 SDN-F 中的轉送路徑。模擬結果表明，我們提出的 IHSF 解決方案在網路可觀測時間、幹擾流數量、端到端延遲和封包傳遞率方面比現有方法具有更好的性能。