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Snapshots
Published in Preston de Guise, Data Protection, 2020
We typically refer to snapshots as representing on-platform protection. This refers to the concept that the platform being protected is providing the protection mechanism itself. Particularly when we consider traditional storage platforms (SAN and NAS), snapshots are used often to provide protection within the same storage system—a NAS home drive share, for instance, may have many snapshots on the same storage system providing granular recovery for several days. However, since there is no interoperability standard for snapshots between storage vendors, we also equally define replicated snapshots as being on-platform as well: they will be for logically similar storage, either from a storage virtualization perspective, or as two storage arrays from the same vendor. These are defined as on-platform still because the control process for the snapshots is still tied to the data being protected: the control mechanism is on the same platform.
Snapshots
Published in Preston de Guise, Data Protection, 2017
Snapshots frequently offer a very efficient mechanism of achieving low recovery time objectives. In certain disaster recovery situations, a volume or virtual machine that has been snapshot can be “rolled back” considerably faster than, say, complete restoration from a traditional backup. Equally in many circumstances a snapshot can be quickly accessed to retrieve data from it rather than executing a more formal recovery process from a traditional backup system.
An Optimal Time-Based Resource Allocation for Biomedical Workflow Applications in Cloud
Published in IETE Journal of Research, 2022
N. Mohanapriya, G. Kousalya, P. Balakrishnan
Benefits of using Cloud computing for workflow execution [5]: Dynamic acquisition of additional resources Resource requirement for running workflow application can be scaled automatically through a scheduling component or by following user request without the intervention of service provider.Workflow module configuration The software and specific library packages which are required for the workflow application execution are easily configured without the administrator intervention.Snapshot mechanism Cloud computing provides a scalable and fully configured virtual instances to its user for execution. The snapshot techniques facilitate the researchers to store the instance used for workflow analysis as snapshot image for reuse, which enables the user to recreate the analysis during the process of dataset updation or to recreate the original analysis.
Parallelization of the FICO Xpress-Optimizer
Published in Optimization Methods and Software, 2018
Timo Berthold, James Farmer, Stefan Heinz, Michael Perregaard
There are two fundamentally different types of global data: pooled data and updated data. With pooled data, we refer to a set of independent pieces of data, such as feasible solutions, cuts, or conflict constraints. The only difference between a static synchronization at certain synchronization points and a dynamic synchronization with deterministic stamps is that each of the information pieces needs to receive an individual stamp. This poses challenges for both types of data. For pooled data, we need to present different views of the entire pool and of individual items therein. For updated data, i.e. scalar statistics such as counters, averages, and so forth, we need to maintain different update steps or to compute varying aggregations of the underlying data. In either case, this requires being able to present different snapshots of the overall data for different deterministic stamps. Taking snapshots affects the data that is in the read window, everything before the earliest read barrier will be the same in every snapshot and can hence be ‘consolidated’, see above. Obviously, snapshots can be expected to be requested quite frequently; therefore, taking data snapshots needs to be implemented very efficiently to not create significant computational overhead.