SummaryVideo streaming has emerged as a killer application in today's Internet, delivering a tremendous amount of media contents to millions of users at any given time. Such a heavy traffic load demands an effective routing method. In this paper, an effective routing method, named GA-SDN, is developed based on software defined network (SDN) technique. To facilitate the researchers in this field to evaluate the video delivery quality over SDN, an evaluation framework and its associated source codes are provided. The framework integrates the H.264 Scalable Video coding streaming Evaluation Framework (SVEF) with the Mininet emulator. Through this framework, video processing researchers can evaluate their proposed coding algorithms in an SDN-enabled network emulator, while network operators or executives can evaluate the impact of real video streams on the developing network architectures or protocols. Experiment results demonstrate the usefulness of myEvalSVC_SDN and prove that GA-SDN outperforms traditional Bellman-Ford routing algorithm in terms of packet drop rate, throughput, and average peak signal-to-noise ratio.

Industrial wireless sensor networks (IWSNs) are a key technology for smart manufacturing. To identify the performance bottlenecks in an IWSN before its real-world deployment, the IWSN must first be evaluated through simulations using an error model which accurately characterizes the wireless links in the industrial scenario within which it will be deployed. However, the traditional error models used in most IWSN simulators are not derived from the real traces observed in industrial environments. Accordingly, this study first measured the transmission quality of IEEE 802.15.4 in a one-day experiment in a manufacturing factory and then used the measurement records to construct a second-order Markov frame-level error model for simulating the performance of an IWSN. The proposed model was incorporated into the simulator of OpenWSN, which is an industrial WSN implementing the related IEEE and IETF standards. The simulation results showed that the proposed error model improved the accuracy of the estimated transmission reliability by up to 12% compared to the original error model. Moreover, the estimation accuracy improved with increasing burst losses.

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