Prioritized deleting of slices stored in a dispersed storage network
View Patent ↗A method begins by a dispersed storage (DS) processing module monitoring storage of data, wherein the data is encoded using a dispersed storage error coding function to produce a plurality of sets of encoded data slices and is stored as the plurality of sets of encoded data slices. The method continues with the DS processing module determining analysis priority of the data in accordance with an analysis prioritization protocol. When the analysis priority of the data compares unfavorably to a first priority threshold, the method continues with the DS processing module issuing a command to delete an encoded data slice from each set of at least some of the plurality of sets of encoded data slices.
1. A method comprises:
monitoring storage of data, wherein the data is encoded using a dispersed storage error coding function to produce a plurality of sets of encoded data slices and is stored as the plurality of sets of encoded data slices;
determining analysis priority of the data in accordance with an analysis prioritization protocol; and
when the analysis priority of the data compares unfavorably to a first priority threshold, issuing a command to delete an encoded data slice from each set of at least some of the plurality of sets of encoded data slices.
2. The method of claim 1 further comprises:
when the analysis priority of the data compares unfavorably to a second priority threshold, issuing a second command to delete the encoded data slice and at least one other encoded data slice from each set of the at least some of the plurality of sets of encoded data slices.
3. The method of claim 1 further comprises:
determining, in accordance with the analysis prioritization protocol, that analysis of the data is no longer desired; and
when the analysis of the data is no longer desired, issuing a second command to delete the plurality of sets of encoded data slices.
4. The method of claim 1 further comprises:
analyzing the data;
determining, based on the analyzing the data, whether the data can be deleted; and
when the data can be deleted, issuing a second command to delete the plurality of sets of encoded data slices.
5. The method of claim 1 , wherein the analysis priority protocol comprises one or more of:
a time based scaling factor;
a data source based scaling factor;
a data content based scaling factor; and
a data location origination based scaling factor, wherein the analysis priority protocol is a function of the scaling factors.
6. The method of claim 1 further comprises:
determining a data characterization of the data, wherein the data characterization includes at least one of a time factor, a data source factor, a data content factor, and a data location origination factor;
determining a priority level of the data based on the data characterization and the analysis priority protocol; and
selecting parameters for the dispersed storage error coding function based on the priority level.
7. The method of claim 1 further comprises:
when the analysis priority of the data compares unfavorably to the first priority threshold:
issuing a no-rebuilding command regarding the encoded data slices from each set of the at least some of the plurality of sets of encoded data slices; and
updating parameters of the dispersed storage error coding function to reflect the deletion of encoded data slices from each set of the at least some of the plurality of sets of encoded data slices.
8. A dispersed storage (DS) processing module comprises:
a first module, when operable within a computing device, causes the computing device to:
monitor storage of data, wherein the data is encoded using a dispersed storage error coding function to produce a plurality of sets of encoded data slices and is stored as the plurality of sets of encoded data slices;
a second module, when operable within the computing device, causes the computing device to:
determine analysis priority of the data in accordance with an analysis prioritization protocol; and
a third module, when operable within the computing device, causes the computing device to:
when the analysis priority of the data compares unfavorably to a first priority threshold, issue a command to delete an encoded data slice from each set of at least some of the plurality of sets of encoded data slices.
9. The DS processing module of claim 8 , wherein the third module is further operable to:
when the analysis priority of the data compares unfavorably to a second priority threshold, issue a second command to delete the encoded data slice and at least one other encoded data slice from each set of the at least some of the plurality of sets of encoded data slices.
10. The DS processing module of claim 8 , wherein the third module is further operable to:
determine, in accordance with the analysis prioritization protocol, that analysis of the data is no longer desired; and
when the analysis of the data is no longer desired, issue a second command to delete the plurality of sets of encoded data slices.
11. The DS processing module of claim 8 further comprises:
a fourth module, when operable within the computing device, causes the computing device to:
analyze the data; and
the third module, when operable within the computing device, further causes the computing device to:
determine, based on the analyzing the data, whether the data can be deleted; and
when the data can be deleted, issue a second command to delete the plurality of sets of encoded data slices.
12. The DS processing module of claim 8 , wherein the analysis priority protocol comprises at least one of:
a time based scaling factor;
a data source based scaling factor;
a data content based scaling factor; and
a data location origination based scaling factor, wherein the analysis priority protocol is a function of the scaling factors.
13. The DS processing module of claim 8 , wherein the first module is further operable to:
determine a data characterization of the data, wherein the data characterization includes at least one of a time factor, a data source factor, a data content factor, and a data location origination factor;
determine a priority level of the data based on the data characterization and the analysis priority protocol; and
select parameters for the dispersed storage error coding function based on the priority level.
14. The DS processing module of claim 8 , wherein the third module is further operable to:
when the analysis priority of the data compares unfavorably to the first priority threshold:
issue a no-rebuilding command regarding the encoded data slices from each set of the at least some of the plurality of sets of encoded data slices; and
update parameters of the dispersed storage error coding function to reflect the deletion of encoded data slices from each set of the at least some of the plurality of sets of encoded data slices.