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Lossy Scientific Data Compression With SPERR
IEEE International Parallel and Distributed Processing Symposium, 2023As the need for data reduction in high-performance computing (HPC) continues to grow, we introduce a new and highly effective tool to help achieve this goal—SPERR.
Shaomeng Li, P. Lindstrom, J. Clyne
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Adaptive Multivariate Data Compression in Smart Metering Internet of Things
IEEE Transactions on Industrial Informatics, 2021Recent advances in electric metering infrastructure have given rise to the generation of gigantic chunks of data. Transmission of all of these data certainly poses a significant challenge in bandwidth and storage constrained Internet of Things (IoT ...
M. R. Chowdhury, Sharda Tripathi, S. De
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Energy Efficient Data Compression in Cloud Based IoT
IEEE Sensors Journal, 2021In this study, an adaptive data compression scheme (ADCS) is proposed for efficiently controlling the IoT device compression rate and energy consumption in the cloud based IoT network.
Halah Mohammed Al-Kadhim +1 more
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IEEE Transactions on Information Theory, 1994
In a frequent practical situation one possesses inconsistent fragmentary data concerning some industrial process or natural phenomenon. It is an interesting and reasonable task to assess what the most concise way to store or transmit them would be.
KORNER, JANOS, Mario Lucertini
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In a frequent practical situation one possesses inconsistent fragmentary data concerning some industrial process or natural phenomenon. It is an interesting and reasonable task to assess what the most concise way to store or transmit them would be.
KORNER, JANOS, Mario Lucertini
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Data Compression Accelerator on IBM POWER9 and z15 Processors : Industrial Product
International Symposium on Computer Architecture, 2020Lossless data compression is highly desirable in enterprise and cloud environments for storage and memory cost savings and improved utilization I/O and network.
B. Abali +11 more
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Comparison of Lossless Data Compression Techniques
International Congress on Information and Communication Technology, 2020The transmission of humongous data from the monitoring field to the central unit for further processing is a highly challenging task for the hardware, especially when the communication bandwidth is limited.
Athira Gopinath, M. Ravisankar
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Two-Level Data Compression using Machine Learning in Time Series Database
IEEE International Conference on Data Engineering, 2020The explosion of time series advances the development of time series databases. To reduce storage overhead in these systems, data compression is widely adopted.
Xinyang Yu +6 more
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Deep learning for data anomaly detection and data compression of a long‐span suspension bridge
Comput. Aided Civ. Infrastructure Eng., 2019As intelligent sensing and sensor network systems have made progress and low‐cost online structural health monitoring has become possible and widely implemented, large quantities of highly heterogeneous data can be acquired during the monitoring.
FuTao Ni, Jian Zhang, Mohammad Noori
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IEEE Communications Letters, 2019
In this letter, we consider a multiuser mobile-edge computing (MEC) system with latency constraint. In order to meet the latency requirement and save energy consumption, each user can partially offload the task to the MEC server for edge computing.
Ding Xu, Qun Li, Hongbo Zhu
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In this letter, we consider a multiuser mobile-edge computing (MEC) system with latency constraint. In order to meet the latency requirement and save energy consumption, each user can partially offload the task to the MEC server for edge computing.
Ding Xu, Qun Li, Hongbo Zhu
semanticscholar +1 more source