Integer and combinatorial optimization
Integer and combinatorial optimization
OceanStore: an architecture for global-scale persistent storage
ASPLOS IX Proceedings of the ninth international conference on Architectural support for programming languages and operating systems
Minerva: An automated resource provisioning tool for large-scale storage systems
ACM Transactions on Computer Systems (TOCS)
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IPTPS '01 Revised Papers from the First International Workshop on Peer-to-Peer Systems
Evaluation of an Economy-Based File Replication Strategy for a Data Grid
CCGRID '03 Proceedings of the 3st International Symposium on Cluster Computing and the Grid
Disaster Recovery Handbook, The: A Step-by-Step Plan to Ensure Business Continuity and Protect Vital Operations, Facilities, and Assets
Farsite: federated, available, and reliable storage for an incompletely trusted environment
OSDI '02 Proceedings of the 5th symposium on Operating systems design and implementationCopyright restrictions prevent ACM from being able to make the PDFs for this conference available for downloading
QoS-Aware Replica Placement for Content Distribution
IEEE Transactions on Parallel and Distributed Systems
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Proceedings of the 1st ACM SIGOPS/EuroSys European Conference on Computer Systems 2006
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ICESS '08 Proceedings of the 2008 International Conference on Embedded Software and Systems
Automated planners for storage provisioning and disaster recovery
IBM Journal of Research and Development
Disaster recovery as a cloud service: economic benefits & deployment challenges
HotCloud'10 Proceedings of the 2nd USENIX conference on Hot topics in cloud computing
High availability in DHTs: erasure coding vs. replication
IPTPS'05 Proceedings of the 4th international conference on Peer-to-Peer Systems
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In this paper, we present DDP-DR: a Data Distribution Planner for Disaster Recovery. DDP-DR provides an optimal way of backing-up critical business data into data centres (DCs) across several Geographic locations. DDP-DR provides a plan for replication of backup data across potentially large number of data centres so that (i) the client data is recoverable in the event of catastrophic failure at one or more data centres (disaster recovery) and, (ii) the client data is replicated and distributed in an optimal way taking into consideration major business criteria such as cost of storage, protection level against site failures, and other business and operational parameters like recovery point objective (RPO), and recovery time objective (RTO). The planner uses Erasure Coding (EC) to divide and codify data chunks into fragments and distribute the fragments across DR sites or storage zones so that failure of one or more site /zone can be tolerated and data can be regenerated.