Trait based storage unit groups
A method includes selecting a plurality of groups of storage units from a number of storage units based on a plurality of sets of storage pool traits, where a first group of storage units of the plurality of groups of storage units is based on a first set of storage pool traits of the plurality of sets of storage pool traits. The method further includes selecting a storage unit from each of the plurality of groups of storage units in accordance with a selection approach to produce a storage set of selected storage units. The method further includes utilizing the storage set of selected storage units for storing data in the storage network.
1 . A method for execution by one or more computing devices of a storage network, the method comprising:
selecting a plurality of groups of storage units from a number of storage units based on a plurality of sets of storage pool traits, wherein a first group of storage units of the plurality of groups of storage units is based on a first set of storage pool traits;
selecting a storage unit from each of the plurality of groups of storage units in accordance with a selection approach to produce a storage set of selected storage units; and
utilizing the storage set of selected storage units for storing data in the storage network.
2 . The method of claim 1 , wherein the data is dispersed storage error encoded into pluralities of sets of encoded data slices.
3 . The method of claim 1 further comprises:
identifying traits associated with a number of storage units of the storage network to produce identified traits; and
determining the plurality of sets of storage pool traits based on the identified traits, wherein the first set of storage pool traits has a common trait of the identified traits.
4 . The method of claim 3 , wherein the identifying comprises one or more of:
interpreting a list;
initiating a test;
interpreting a test result;
issuing a storage query; and
interpreting a received storage response.
5 . The method of claim 3 , wherein a trait of the traits includes an attribute of a storage unit of the number of storage units that affects availability of the storage unit with respect to other storage units of the number of storage units.
6 . The method of claim 5 , wherein the trait is a common device type.
7 . The method of claim 5 , wherein the trait is a common geographic region.
8 . The method of claim 5 , wherein the trait is a common storage reliability level.
9 . The method of claim 5 , wherein the trait is a common availability timeframe.
10 . The method of claim 3 , wherein the selection approach includes minimizing correlation of the traits between storage units of the storage set of selected storage units.
11 . A computing device of a storage network, the computing device comprising:
memory;
an interface; and
a processing module operably coupled to the memory and the interface, wherein the processing module is operable to:
select a plurality of groups of storage units from a number of storage units based on a plurality of sets of storage pool traits, wherein a first group of storage units of the plurality of groups of storage units is based on a first set of storage pool traits;
select a storage unit from each of the plurality of groups of storage units in accordance with a selection approach to produce a storage set of selected storage units; and
store data in the storage network utilizing the storage set of selected storage units.
12 . The computing device of claim 11 , wherein the processing module is further operable to dispersed storage error encode the data into pluralities of sets of encoded data slices.
13 . The computing device of claim 11 , wherein the processing module is further operable to:
identify traits associated with a number of storage units of the storage network to produce identified traits; and
determine the plurality of sets of storage pool traits based on the identified traits, wherein the first set of storage pool traits has a common trait of the identified traits.
14 . The computing device of claim 13 , wherein the processing module is further operable to performing the identifying by one or more of:
interpreting a list;
initiating a test;
interpreting a test result;
issuing a storage query; and
interpreting a received storage response.
15 . The computing device of claim 13 , wherein the processing module is further operable to determine a trait of the traits includes an attribute of a storage unit of the number of storage units that affects availability of the storage unit with respect to other storage units of the number of storage units.
16 . The computing device of claim 15 , wherein the processing module is further operable to determine the trait is a common device type.
17 . The computing device of claim 15 , wherein the processing module is further operable to determine the trait is a common geographic region.
18 . The computing device of claim 15 , wherein the processing module is further operable to determine the trait is a common storage reliability level.
19 . The computing device of claim 15 , wherein the processing module is further operable to determine the trait is a common availability timeframe.
20 . The computing device of claim 13 , wherein the processing module is further operable to determine the selection approach includes minimizing correlation of the traits between storage units of the storage set of selected storage units.