User Preference Aware Lossless Data Compression at the Edge
نویسندگان
چکیده
منابع مشابه
Data-Aware, Resource-Aware, Lossless Compression for Sensor Networks
Compressing sensor data benefits sensor network applications because compression saves both transmission energy and storage space. This paper presents a novel lossless compression algorithm for sensor networks that is both dataaware and resource-aware. The DARA algorithm provides high compression ratios and also has a small memory footprint and efficient execution well within the range of senso...
متن کاملLossless Compression of Region Edge
In this note, we describe a lossless compression technique that has been applied to bitmaps deening regions of images. The results show considerable improvement over previous methods. The basic technique is to use context-based statistical modeling fed into an arithmetic coder.
متن کاملLossless Data Compression at Finite Blocklengths
This paper provides an extensive study of the behavior of the best achievable rate (and other related fundamental limits) in variable-length lossless compression. In the non-asymptotic regime, the fundamental limits of fixed-to-variable lossless compression with and without prefix constraints are shown to be tightly coupled. Several precise, quantitative bounds are derived, connecting the distr...
متن کاملLossless Compression of Region Edge Maps Lossless Compression of Region Edge Maps
In this note, we describe a lossless compression technique that has been applied to bitmaps deening regions of images. The results show considerable improvement over previous methods. The basic technique is to use context-based statistical modeling fed into an arithmetic coder.
متن کاملLZAC Lossless Data Compression
This paper presents LZAC, a new universal lossless data compression algorithm derived from the popular and widely used LZ77 family. The objective of LZAC is to improve the compression ratios of the LZ77 family while still retaining the family’s key characteristics: simple, universal, fast in decoding, and economical in memory consumption. LZAC presents two new ideas: composite fixed-variable-le...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Communications
سال: 2020
ISSN: 0090-6778,1558-0857
DOI: 10.1109/tcomm.2020.2978072