Reducing Read Latency of Shingled Magnetic Recording With Severe Intertrack Interference Using Transparent Lossless Data Compression

2013 ◽  
Vol 49 (8) ◽  
pp. 4761-4767 ◽  
Author(s):  
Kalyana Sundaram Venkataraman ◽  
Guiqiang Dong ◽  
Ningde Xie ◽  
Tong Zhang
Keyword(s):  
Data Compression ◽  
Magnetic Recording ◽  
Shingled Magnetic Recording ◽  
Lossless Data Compression ◽  
Intertrack Interference

Intertrack Interference Cancellation for Shingled Magnetic Recording

2011 ◽  
Vol 47 (10) ◽  
pp. 3698-3703 ◽  
Author(s):  
Erich F. Haratsch ◽  
George Mathew ◽  
Jongseung Park ◽  
Ming Jin ◽  
Kurt J. Worrell ◽  
...  
Keyword(s):  
Magnetic Recording ◽  
Interference Cancellation ◽  
Shingled Magnetic Recording ◽  
Intertrack Interference

Enabling Sequential-write-constrained B + -tree Index Scheme to Upgrade Shingled Magnetic Recording Storage Performance

2019 ◽  
Vol 18 (5s) ◽  
pp. 1-20
Author(s):  
Yu-Pei Liang ◽  
Tseng-Yi Chen ◽  
Yuan-Hao Chang ◽  
Shuo-Han Chen ◽  
Kam-Yiu Lam ◽  
...  
Keyword(s):  
Magnetic Recording ◽  
Storage Performance ◽  
Shingled Magnetic Recording ◽  
Tree Index

Joint Source-Channel Coding in Dictionary Methods of Lossless Data Compression

2010 ◽  
Vol 56 (4) ◽  
pp. 351-355
Author(s):  
Marcin Rodziewicz
Keyword(s):  
Data Compression ◽  
Channel Coding ◽  
Data Stream ◽  
Noisy Channels ◽  
Error Resiliency ◽  
Joint Source Channel Coding ◽  
Lossless Data Compression ◽  
Compressed Data ◽  
Source Channel Coding

Joint Source-Channel Coding in Dictionary Methods of Lossless Data Compression Limitations on memory and resources of communications systems require powerful data compression methods. Decompression of compressed data stream is very sensitive to errors which arise during transmission over noisy channels, therefore error correction coding is also required. One of the solutions to this problem is the application of joint source and channel coding. This paper contains a description of methods of joint source-channel coding based on the popular data compression algorithms LZ'77 and LZSS. These methods are capable of introducing some error resiliency into compressed stream of data without degradation of the compression ratio. We analyze joint source and channel coding algorithms based on these compression methods and present their novel extensions. We also present some simulation results showing usefulness and achievable quality of the analyzed algorithms.

Signal Model for Shingled Magnetic Recording Based on Data Dependent Erase Band Analysis Under Track Squeeze

2013 ◽  
Vol 49 (2) ◽  
pp. 734-738 ◽  
Author(s):  
Euiseok Hwang ◽  
Ming Jin ◽  
Jongseung Park ◽  
Erich F. Haratsch ◽  
Ivana Djurdjevic ◽  
...  
Keyword(s):  
Magnetic Recording ◽  
Signal Model ◽  
Shingled Magnetic Recording

Optimal Lossless Data Compression Methodology

2021 ◽  
Author(s):  
Sanjana Rao ◽  
Vidyashree T S ◽  
Manasa M ◽  
Bindushree V ◽  
C. Gururaj
Keyword(s):  
Data Compression ◽  
Lossless Data Compression
Sign in / Sign up

Export Citation Format

Share Document