DocumentCode :
2792661
Title :
Combining Compression, Encryption and Fault-tolerant Coding for Distributed Storage
Author :
Sobe, Peter ; Peter, Kathrin
Author_Institution :
Inst. of Comput. Eng., Univ. of Luebeck
fYear :
2007
fDate :
26-30 March 2007
Firstpage :
1
Lastpage :
8
Abstract :
Storing data in distributed systems aims to offer higher bandwidth and scalability than storing locally. But, a couple of disadvantageous issues must be taken into account such as unreliability caused by faults, temporal downtimes and malicious attacks. To improve dependability, redundancy codes like parity can be used as well as more sophisticated codes such as Reed/Solomon. Another issue-security requirements-arise when data is kept in untrusted units in a network. To encrypt data, it is common to use security algorithms like AES. For efficient transfer and storage, the amount of data can be reduced by compression algorithms. All these techniques-data distribution, fault-tolerant coding, encryption and compression-can be employed together using independent algorithms, but in a proper combination. A superposition of these techniques exploiting synergies is still an issue for research. Thus, in this paper we study proper technique combinations applied to distributed storage. The combinations are classified and examined with respect to their potential benefit and limitations. For our model, performance parameters from the distributed storage system NetRAID are used.
Keywords :
Reed-Solomon codes; cryptography; data compression; fault tolerant computing; redundancy; storage management; AES security algorithms; NetRAID distributed storage system; Reed-Solomon codes; data compression; data encryption; distributed data storage; fault-tolerant coding; malicious attacks; parity codes; redundancy codes; Cryptography; Data security; Distributed computing; Fault tolerance; Fault tolerant systems; Image coding; Image storage; Network servers; Redundancy; Secure storage;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel and Distributed Processing Symposium, 2007. IPDPS 2007. IEEE International
Conference_Location :
Long Beach, CA
Print_ISBN :
1-4244-0910-1
Electronic_ISBN :
1-4244-0910-1
Type :
conf
DOI :
10.1109/IPDPS.2007.370611
Filename :
4228339
Link To Document :
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