SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
PRINS: Optimizing Performance of Reliable Internet Storages
ICDCS '06 Proceedings of the 26th IEEE International Conference on Distributed Computing Systems
Design And Analysis of Reliable And Fault-tolerant Computer Systems
Design And Analysis of Reliable And Fault-tolerant Computer Systems
Bigtable: a distributed storage system for structured data
OSDI '06 Proceedings of the 7th USENIX Symposium on Operating Systems Design and Implementation - Volume 7
Dynamo: amazon's highly available key-value store
Proceedings of twenty-first ACM SIGOPS symposium on Operating systems principles
MapReduce: simplified data processing on large clusters
Communications of the ACM - 50th anniversary issue: 1958 - 2008
BackupIT: An Intrusion-Tolerant Cooperative Backup System
ICIS '09 Proceedings of the 2009 Eigth IEEE/ACIS International Conference on Computer and Information Science
Introduction to Algorithms, Third Edition
Introduction to Algorithms, Third Edition
Performance Evaluation of a Chord-Based JXTA Implementation
AP2PS '09 Proceedings of the 2009 First International Conference on Advances in P2P Systems
The Hadoop Distributed File System
MSST '10 Proceedings of the 2010 IEEE 26th Symposium on Mass Storage Systems and Technologies (MSST)
REST in Practice: Hypermedia and Systems Architecture
REST in Practice: Hypermedia and Systems Architecture
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Cloud computing is a computing model where hardware, platforms and software are seen as services; viz. Infrastructure as a Service, Platform as a Service, and Software as a Service, respectively. Data as a Service (DaaS) is based on the concept that the product, data in this case, can be provided on demand to the user, regardless of geographic or organizational separation between provider and consumer. DaaS applications are for the most part based on excessive data replication in order to guarantee data availability, which means excessive costs in hardware investments. This white paper presents the specification, implementation and evaluation of a system called USTO.RE which aims to be an effective and low-cost alternative for storing data, thereby mitigating the problem of excessive data replication and thus allows itself to be considered a reliable platform from the perspective of data availability. Evaluation scenarios and the results achieved in our experiments to evaluate the system as well as possible lines for future development will be presented.