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In this paper, we introduce a token-based GPU scheduler that enhances the utilization of GPU usage in heterogeneous CPU/GPU big data cluster. The cluster is managed by a big data framework such as Hadoop, Spark, or Storm to provide the necessary processing scalability and flexibility. Enabling computer vision or video processing application in big data cluster is very computationally expensive and...
This paper presents an efficient image restoration algorithm that is content adaptive. Traditional image restoration or de-blurring algorithms apply the same logic on the whole image even when only few image blocks are blurry. The developed algorithm is designed to use less calculations and save the un-blurred image parts quality during the de-blurring process. When more than one image is used, our...
In this paper, we present a dynamic framework for P2P video streaming using dynamic adaptive streaming over HTTP (DASH). DASH is a very popular standard and is expected to dominate the adaptive streaming market. Our proposed framework defines several components; DASH Session Coordinator (DSC), Intelligent Content Server (ICS), and Adaptive Streaming Client (ASC). Each component has a defined set of...
In this paper we discuss the potential effects of using various segment durations of the available contents within a simulated mobile environment. OPNET modeler was used to implement a real-time test platform for mobile video streaming using OPNET system in the loop component (SITL). The real-time test platform was then used to evaluate the performance of the requests for different segment size. Dynamic...
This paper presents a technical analysis on live P2P streaming techniques. The paper provides an overview on existing P2P solutions with more focus on solutions proposed for Dynamic Adaptive Streaming over HTTP (DASH). DASH is currently the state of the art protocol for adaptive streaming. The paper highlights the gains and challenges of live P2P streaming and discusses how P2P streaming serves as...
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