LT Codes For Efficient and Reliable Distributed Storage Systems Revisited
Yongge Wang

TL;DR
This paper analyzes the use of LT codes in distributed storage, introducing new code classes and theoretical insights to improve efficiency and reliability, especially for small data fragments.
Contribution
It introduces flat and array BP-XOR codes as deterministic variants of LT codes, establishing their equivalence with edge-colored graph models for better design and analysis.
Findings
Array BP-XOR codes can be designed using graph theory.
Edge-colored graph models are equivalent to array BP-XOR codes.
Theoretical analysis supports efficient LT code application in storage systems.
Abstract
LT codes and digital fountain techniques have received significant attention from both academics and industry in the past few years. There have also been extensive interests in applying LT code techniques to distributed storage systems such as cloud data storage in recent years. However, Plank and Thomason's experimental results show that LDPC code performs well only asymptotically when the number of data fragments increases and it has the worst performance for small number of data fragments (e.g., less than 100). In their INFOCOM 2012 paper, Cao, Yu, Yang, Lou, and Hou proposed to use exhaustive search approach to find a deterministic LT code that could be used to decode the original data content correctly in distributed storage systems. However, by Plank and Thomason's experimental results, it is not clear whether the exhaustive search approach will work efficiently or even correctly.…
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Taxonomy
TopicsAdvanced Data Storage Technologies · Caching and Content Delivery · Error Correcting Code Techniques
