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Titlebook: Algorithms and Architectures for Parallel Processing; 20th International C Meikang Qiu Conference proceedings 2020 Springer Nature Switzerl

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E. Möller-Arnold,E. Feichtingernt network systems with high Quality of Service (.) guarantee. In this paper, an optimal replica placement problem is formulated in terms of minimizing the replica placement cost subject to both . and fault-tolerant constraints. Based on the generalized graph model, the optimal replica placement pro
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Der Felsbau, Band 1, Theoretischer Teilatly helps Earth scientists on their research, conducting data processing and analytics from the data is getting more and more time consuming and complicated. One common data processing task is to aggregate satellite observation data from original pixel level to latitude-longitude grid level to easi
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https://doi.org/10.1007/978-3-662-58194-0en dedicated to algorithms and optimizations in the cloud-edge data cache and computation offloading schemes, while there is a blank in practical implementation to facilitate such a paradigm. In this work, we proposed a component-based framework that facilitates dynamic partitioning of a software pr
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Leopold Müller-Salzburg,Edwin Feckerd high quality of service (QoS) requirements. However, the mobility of end users in smart city systems can result in considerable network performance and QoS degradation, hence interrupting fog services provisioning. . is considered an effective solution to avoid service interruption and ensure serv
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https://doi.org/10.1007/978-3-662-58192-6orage costs. It is difficult to deploy this model on embedded systems. Therefore, model compress is a popular solution to reduce the above overheads. In this paper, a new filter pruning method based on the clustering algorithm is proposed to compress network models. First, we perform clustering with
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https://doi.org/10.1007/978-3-662-58198-8 achieved through single vehicle sensors, such as a camera or LiDAR. Consider the low cost and wide application of optical cameras, a simple image segmentation-based on-road object tracking model is proposed. Different from the detection-based tracking with bounding box, our model improves tracking
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