Reliability analysis of distributed storage systems considering data loss and theft

Author(s):  
Heping Jia ◽  
Rui Peng ◽  
Yi Ding ◽  
Changzheng Shao

With the advancement of cloud computing and internet of things, data are usually stored on distributed computers and these data may risk being lost or stolen. In this article, we consider a common case where the entirety of the data is partitioned into several parts and each data part can be allocated to one or more computers. In the case where a computer fails, all the data parts on it are lost. Before the failure of any computer, the data parts may also be stolen by hackers. The basic model of computer failure and computer intrusion resulting in the theft of all the data parts on the computer is considered first. Then, the case is extended to a general model where computer failure, as well as data part corruption and theft caused by hacking are embedded. It is essential to study the reliability of distributed storage systems considering both data loss and data theft, which can be a basis for decision making on system structure optimization. In this article, a multi-valued decision diagram–based approach is developed to quantitatively evaluate system reliability for both models considering the time-dependence property of sequential events. The proposed method is applicable to systems where the random time to failure, theft, or corruption follows arbitrary distributions including the commonly used exponential distributions. Illustrative examples are provided to validate the proposed method.

2014 ◽  
Vol 918 ◽  
pp. 295-300
Author(s):  
Peng Fei You ◽  
Yu Xing Peng ◽  
Zhen Huang ◽  
Chang Jian Wang

In distributed storage systems, erasure codes represent an attractive data redundancy solution which can provide the same reliability as replication requiring much less storage space. Multiple data losses happens usually and the lost data should be regenerated to maintain data redundancy in distributed storage systems. Regeneration for multiple data losses is expected to be finished as soon as possible, because the regeneration time can influence the data reliability and availability of distributed storage systems. However, multiple data losses is usually regenerated by regenerating single data loss one by one, which brings high entire regeneration time and severely reduces the data reliability and availability of distributed storage systems. In this paper, we propose a tree-structured parallel regeneration scheme based on regenerating codes (TPRORC) for multiple data losses in distributed storage systems. In our scheme, multiple regeneration trees based on regenerating code are constructed. Firstly, these trees are created independently, each of which dose not share any edges from the others and is responsible for one data loss; secondly, every regeneration tree based on regenerating codes owns the least network traffic and bandwidth optimized-paths for regenerating its data loss. Thus it can perform parallel regeneration for multiple data losses by using multiple optimized topology trees, in which network bandwidth is utilized efficiently and entire regeneration is overlapped. Our simulation results show that the tree-structured parallel regeneration scheme reduces the regeneration time significantly, compared to other regular regeneration schemes.


2017 ◽  
Vol 45 (1) ◽  
pp. 51-51
Author(s):  
Wen Sun ◽  
Véronique Simon ◽  
Sébastien Monnet ◽  
Philippe Robert ◽  
Pierre Sens

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