Paper Info
Title
Adaptive erasure code based distributed storage systems
Abstract
Consider the following scenario: A data storage service provider provides an erasure code based distributed storage system (DSS). For the same data, the service provider gives several options: an (n <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> , k <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> ) erasure code based DSS for i = 1,2, ..., m. The service provider charges differently for different options (say dollar Pi for an (n <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> , k <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> ) erasure code based DSS for the data B of size |B|). A client had initially chosen for an (n <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> , k <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> ) erasure code based DSS. At some point of time, the client wants to change for another option, say for an (n <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">j</sub> , k <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">j</sub> ) erasure code based DSS for the same data, where 1≤ i, j ≤ m, i ≠ j. Thus, service provider would require to convert the (n <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> , k <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> ) erasure code based DSS into an (n <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">j</sub> , k <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">j</sub> ) erasure code based DSS. The service provider has the following problem: How to design an erasure code based DSS so that the conversion of an (n <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> , k <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> ) erasure code based DSS into an (n <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">j</sub> , k <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">j</sub> ) erasure code based DSS, for 1 ≤ i, j ≤ m, i ≠ j, can be done by downloading the minimum amount of data? In this paper, we present an adaptive coding scheme which requires to download the minimum amount of data while converting an (n <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> , k <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">i</sub> ) erasure code based DSS to an (n <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">j</sub> , k <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">j</sub> ) erasure code based DSS, where 1 ≤ i, j ≤ m, i ≠ j.
Year
DOI
Venue
2015
10.1109/CWIT.2015.7255179
2015 IEEE 14th Canadian Workshop on Information Theory (CWIT)
Keywords
Field
DocType
adaptive coding scheme,erasure code based DSS,service provider,data storage service provider,adaptive erasure code based distributed storage systems
Discrete mathematics,Code rate,Computer science,Upload,Distributed data store,Theoretical computer science,Service provider,Erasure code,Encoding (memory),Spread spectrum,Adaptive coding
Conference
Citations 
PageRank 
References 
1
0.36
12
Authors
1
Name
Order
Citations
PageRank
Brijesh Kumar Rai19513.98