Titlebook: Edge Computing – EDGE 2018; Second International Shijun Liu,Bedir Tekinerdogan,Liang-Jie Zhang Conference proceedings 2018 Springer Interna

性学院

FCN-biLSTM Based VAT Invoice Recognition and Processingachieve higher accuracy. Combined with the previous text detection methods and the attention-based biLSTM sequence learning structure for text recognizing, we developed an automatic VAT invoice recognition and processing system. The system in the actual projects of enterprises has achieved impressive performance.

tolerance

Mobile Edge Offloading Using Markov Decision Processesand data should be automatically shifted between mobile devices, the edge, and the cloud. To address this issue, this study proposes a Markov Decision Process (MDP) based methodology to intelligently make such choices while optimizing multiple objectives. Results demonstrate an 17.47% or greater increase in performance.

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Employee

Research on Cross-Chain Technology Based on Sidechain and Hash-Lockingat is cross-chain and elaborates the principles and cases of multi-signature wallet. Then it focuses on analyzing the current significant cross-chain technology and successful cross-chain projects. Finally, this article explores a new cross-chain solution.

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0302-9743 zed in topical sections named: Research Track; Application and Industry Track; and Short Paper Track. They deal with the latest fundamental advances in the state of the art and practice of edge computing..978-3-319-94339-8978-3-319-94340-4Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Pander

Modular Framework for Data Prefetching and Replacement at the Edge consumption of edge devices when interacting with the cloud to retrieve the needed data. The framework can be implemented either directly as a real cache, or as a virtual cache that acts as an advisor to the real cache. The latter strategy is useful when the real cache already exists and deals with

Expressly

Boundless Application and Resource Based on Container Technologyon of cloud computing, providing features to solve problems of cloud computing. However, edge computing is unstable and not enough reliable at present. Orchestration may occur occasionally in order to meet the need of the users. This paper provides an architecture named Boundless Resource Orchestrat

同位素

A Reconfigurable Streaming Processor for Real-Time Low-Power Execution of Convolutional Neural Netwo to the edge of the network near the data producers and sensors. Edge analytics are essential for real-time video analytics and situational awareness; which is required for the wide range of cyber-physical applications such as smart transportation, smart cities, and smart health. To this end, novel

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