Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/466432
Title: | Erasure Codes for Distributed Storage Tight Bounds and Matching Constructions |
Researcher: | Balaji, S B |
Guide(s): | Vijay Kumar, P |
Keywords: | Engineering Engineering and Technology Engineering Electrical and Electronic |
University: | Indian Institute of Science Bangalore |
Completed Date: | 2018 |
Abstract: | The reliable storage of Big Data across a spatially distributed network of nodes, calls for erasure-correcting codes that in addition to protecting against data loss, can also efficiently handle node repair. The need for node repair could arise on account of device failure, need for a maintenance reboot, or simply because the node is busy serving other demands. An important consideration here is the rate of the code, which is the ratio of the number of data symbols to the total amount of storage needed to reliably store these data symbols. In response, coding theorists have come up with two new classes of codes, known respectively as regenerating codes and Locally Recoverable Codes (LRC). While the focus of the thesis is on LRC, there are also contributions to the theory of regenerating codes. Contributions to LRC: A LRC is quite simply, a code where a given code symbol can be recovered by contacting at most r other code symbols, where the parameter r is much smaller than the dimension k of the code. A LRC with sequential recovery, is a code that can recover from an arbitrary set of trerasures in t steps in a sequential fashion. Each step recovers an erased symbol and makes use of at most r other code symbols comprising of unerased symbols as well as previously recovered symbols. In this thesis, a tight upper bound on the rate of LRC with sequential recovery is provided, for any value of the number t of erasures and any value of the locality parameter r and#8805; 3. This bound proves an earlier conjecture due to Song, Cai and Yuen. While the bound is valid irrespective of the field over which the code is defined, a matching construction of binary codes that achieve the upper bound on rate is also presented. Contributions to Regenerating Codes: Regenerating codes aim to minimize the amount of data download needed to repair a failed node. Regenerating codes are linear codes that operate over a vector alphabet, i.e., each code symbol in a regenerating code is a vector of and#945; symbols drawn from a field F. An important open ... |
Pagination: | |
URI: | http://hdl.handle.net/10603/466432 |
Appears in Departments: | Electrical Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
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01_title page.pdf | Attached File | 113.08 kB | Adobe PDF | View/Open |
02_prelim pages.pdf | 476.69 kB | Adobe PDF | View/Open | |
03_table of content.pdf | 158.32 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 165.33 kB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 1.21 MB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 622.61 kB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 961.54 kB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 450.64 kB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 787.16 kB | Adobe PDF | View/Open | |
10_chapter 6.pdf | 824.61 kB | Adobe PDF | View/Open | |
11_chapter 7.pdf | 326.64 kB | Adobe PDF | View/Open | |
12_annexure.pdf | 449.44 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 105.42 kB | Adobe PDF | View/Open |
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