Emc IP Holding Company LLC

Other

Jin Ru Yan

Mengze Liao

Jing Yu

Weiyang Liu

Zhen Jia

Zijia Wang

Ming Zhang

Jiacheng Ni

Qi Rong Wang

Yasemin Ugur-Ozekinci

Qi Wang

Chenxi Hu

Scott Randolph Quesnelle

Yongsheng Guo

Xuwei Tang

Yuanyi Liu

Mike Xiaoliang Zhu

Zengjie Zhang

Embodiments of the present disclosure relate to a method, a device and a computer program product for recovering data. The method comprises in response to receiving a request to recover data from a backup node to a source node, determining a plurality of candidate backup nodes having copies of the data; determining respective performance indicators of the plurality of candidate backup nodes; and determining, from the plurality of candidate backup nodes, the backup node for recovering the data to the source node based on the respective performance indicators of the plurality of candidate backup nodes.

Method, apparatus and computer program product for recovering data

A current retention mode is identified as being one of conservative or aggressive. When the retention mode is identified as aggressive, a check is made as to whether used space on backup storage is below a lower threshold. If the used space is below the lower threshold, a switch is made into the conservative mode. If the used space is above the lower threshold, the aggressive mode is maintained. While in the aggressive mode, a backup chain of a database is selected for pruning, the selected backup chain having a shortest retention term of all backup chains not yet pruned and not being a latest backup chain. Log backups of the database in the selected backup chain are identified. Each log backup that has expired is deleted regardless of dependency of other backups on an expired log backup.

Self-adaptive copy retention management

According to embodiments of the present disclosure, a method, device and computer program product for storage management are proposed. The method comprises: obtaining, in a first virtual storage device, a first portion storing a source file, the source file being used to update a target file; determining a second portion in the first virtual storage device, data stored in the second portion being changed relative to data stored in a second virtual storage device, the data stored in the second virtual storage device including the target file; determining a changed portion based on the first portion and the second portion, the changed portion indicating changed data of the source file relative to the target file; and updating the target file based on the changed portion. Therefore, the present solution can reduce data transmission and resource consumption.

Method, device and computer program product for storage management

Embodiments of the present disclosure relate to a method, an electronic device, and a computer program product for backing up data. The method comprises: determining historical information of a storage space for backing up the data, the historical information indicating a historical size of the storage space configured to store the data within a historical time period, a size of the data being changeable within the historical time period; determining change information of the historical size of the storage space based on the historical information; determining, based on the change information, a probability that a size of the storage space to be configured to back up the data reaches a predetermined size; and adjusting, based on a determination that the probability is higher than or equal to a predetermined threshold, a backup policy for backing up the data to reduce the probability. By using the technical solution of the present disclosure, a backup system can pre-adjust a backup policy by determining a change trend of use of a storage space for backing up data, so that a backup failure will not be caused by an insufficient storage space, and an original backup policy can be recovered automatically when a size of the storage space is increased.

Method, electronic device, and computer program product for backing up data

Embodiments of the present disclosure relate to a model training method, a data processing method, an electronic device, and a computer program product. The method includes: acquiring storage information associated with a simulated network environment; and training a reinforcement learning model using simulated data and based on a simulated-data read request for a node among multiple nodes included in the simulated network environment and each having a cache. With the technical solutions of the present disclosure, the cache allocation and cache replacement problems can be simultaneously solved by using a reinforcement learning model to determine in a dynamic environment a data caching scheme that meets predetermined criteria, so that it is possible to not only improve the accuracy and efficiency of determining the data caching scheme with less cost overhead, but also improve the user experience of users using the caching system.

Model training method, data processing method, electronic device, and program product

The present invention relates to a preparation method of fluorinated graphene. The method for preparing fluorinated graphene, including the following steps: S1), under the protection of inert gas, the graphene undergoes a fluorination reaction with a first fluorinating agent, the reaction temperature is 150-550&#xb0; C., the reaction time is 2-20 h, and a fluorinated graphene crude product is obtained. The graphene is graphene powder, or a graphene film; the first fluorinating agent includes fluorine gas; S2), under the protection of inert gas, the fluorinated graphene crude product undergoes a fluorination reaction with a second fluorinating agent, the reaction temperature is 150-400&#xb0; C., the reaction time is 2-10 h, and a fluorinated graphene is obtained. The second fluorinating agent is gas-phase fluoride. By using the method, fluorinated graphene having a high fluorine content can be prepared, the fluorine content is close to the theoretical level, and the defect density is low.

Fluorinated graphene and preparation method thereof

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Shanghai, China

Jin Ru Yan