Titlebook: Edge Computing – EDGE 2020; 4th International Co Ajay Katangur,Shih-Chun Lin,Liang-Jie Zhang Conference proceedings 2020 Springer Nature Sw

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Edge Architecture for Dynamic Data Stream Analysis and Manipulation, compute platforms. Edge compute tasks largely involve sending data from an edge compute device to a central location where data is processed and returned to the edge device as a response. Since most edge network infrastructure is restricted in its ability to dynamically delegate computation while r

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fogcached: DRAM-NVM Hybrid Memory-Based KVS Server for Edge Computing,loud servers but also on or near interactive devices to store their data with low latency access. To satisfy these requirements, we consider a new edge computing system that consists of a hybrid main memory with a KVS (Key-Value-Store) server utilizing the DRAM and nonvolatile main memory (NVM). It

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Small, Accurate, and Fast Re-ID on the Edge: The SAFR Approach,, or embedded devices by only changing the re-id model backbone. Through best-fit design choices, feature extraction, training tricks, global attention, and local attention, we create a re-id model design that optimizes multi-dimensionally along model size, speed, & accuracy for deployment under var

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Edge Storage Solution Based on Computational Object Storage,e the data is captured). Computational storage, defined as an architecture that conducts data processing at the storage layer so as to offload host processing or reduce data movement, allows raw data to be analyzed as the data are stored. As a consequence, the data to be stored may intrinsically car

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,Preserving Patients’ Privacy in Medical IoT Using Blockchain,re used to track individuals’ medical conditions. The collected data is processed, analyzed, and stored in the cloud platforms to provide healthcare services. The data does not only include personal information like users’ identity and location but also consists of sensitive information such as ment

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