Method of determining lower bound for replication cost

• US 20050283487A1
• Filed: 06/21/2004
• Published: 12/22/2005
• Est. Priority Date: 06/21/2004
• Status: Abandoned Application

• Current Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Original Assignee: Hewlett-Packard Development Company, L.P. (HP Inc.)
• Inventors: Karlsson, Magnus, Karamanolis, Christos
• Application Number:
  US10/873,994
• Publication Number:
  US 20050283487A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 3/0608 Saving storage space on storage systems
• CPC Class Codes: G06F 3/0617 in relation to availability
• CPC Class Codes: G06F 3/0619 in relation to data integrity, e.g. data losses, bit errors
• CPC Class Codes: G06F 3/065 Replication mechanisms
• CPC Class Codes: G06F 3/067 Distributed or networked storage systems, e.g. storage area networks [SAN], network attached storage [NAS]
• CPC Class Codes: H04L 67/1095 Replication or mirroring of data, e.g. scheduling or transport for data synchronisation between network nodes

Abstract

An embodiment of a method of determining a lower bound for a minimum cost of placing data objects onto nodes of a distributed storage system begins with a first step of assigning a placement of a data object to a node and a time interval which meets a benefit criterion. Assignment of the placement of the data object to the node and the time interval comprises assigning the placement of the data object to a node-interval. The method continues with a second step of continuing to assign additional placements of the data object to other node-intervals which each meet the benefit criterion until a performance reaches a performance threshold. The method performs the first and second steps for each of the data objects. The method concludes with a step of calculating a sum of storage costs and creation costs for the placement and the additional placements of the data objects. According to another embodiment, the data object placed in the first and second steps is chosen on a basis of a triplet of the data object, the node, and the interval which meets the benefit criterion.

Claims

1. A method of determining a lower bound for a minimum cost of placing data objects onto nodes of a distributed storage system comprising the steps of:

for each data object, assigning a placement of the data object to a node and a time interval which meets a benefit criterion, thereby assigning the placement of the data object to a node-interval;

for each data object, continuing to assign additional placements of the data object to other node-intervals which each meet the benefit criterion until a performance reaches a performance threshold; and

calculating a sum of storage costs and creation costs for the placement and the additional placements of the data objects.

2. The method of claim 1 wherein the benefit criterion comprises the node and the time interval for which a ratio of covered demand to a placement cost for the placement of the data object is maximal.

3. The method of claim 1 wherein the benefit criterion comprises the node and the time interval for which a number of covered nodes is maximal.

4. The method of claim 1 wherein the step of assigning the placement of the data object to the node-interval comprises determining a candidate time interval for placing the data object onto each node that provides a maximum nodal benefit for the node.

5. The method of claim 4 wherein the step of assigning the placement of the data object to the node-interval further comprises:

assigning a placement of the data object onto the node for the candidate time interval which meets the benefit criterion, thereby reducing non-placement time intervals for the node by the candidate time interval; and

determining a new candidate time interval for the node selected from the non-placement time intervals, the new candidate time interval providing the maximum nodal benefit.

6. The method of claim 5 wherein the step of continuing to assign the additional placements of the data object to the other node-intervals until the performance reaches the performance threshold comprises iteratively:

assigning the placement of the data object onto the node for the candidate time interval which meets the benefit criterion; and

determining the new candidate time interval for the node.

7. The method of claim 1 further comprising the step of identifying a minimal number of non-overlapping sets which cover the nodes in the distributed storage system, each non-overlapping set comprising an effective node.

8. The method of claim 7 wherein the step of assigning the placement of the data object to the node and the time interval comprises assigning the placement of the data object to a particular effective node and the time interval, thereby assigning the data object to an effective node-interval.

9. The method of claim 8 wherein the step of continuing to assign the additional placements of the data object to the other node-intervals comprises continuing to assign the additional placements of the data object to other effective node-intervals until the performance reaches the performance threshold.

10. The method of claim 1 wherein the performance threshold comprises a specified ratio of successful accesses to total accesses.

11. The method of claim 1 wherein the performance threshold comprises a specified average latency.

12. The method of claim 1 wherein the performance threshold comprises a specified latency percentile.

13. The method of claim 1 further comprising the steps of:

determining a particular node which uses a maximum amount of storage within any time interval; and

allocating the maximum amount of storage on all nodes for all time intervals.

14. The method of claim 1 further comprising the steps of:

determining a maximum amount of storage for each node within any time interval; and

allocating the maximum amount of storage on each node for all time intervals.

15. The method of claim 1 further comprising the steps of:

determining a maximum number of replicas for any data object within any time interval; and

assigning the maximum number of replicas for all data objects for all time intervals.

16. The method of claim 1 further comprising the steps of:

determining a maximum number of replicas for each data object within any time interval; and

assigning the maximum number of replicas for each data object for all time intervals.

17. A method of determining a lower bound for a minimum cost of placing data objects onto nodes of a distributed storage system comprising the steps of:

assigning a placement of a data object to a node and a time interval for which the data object, the node, and the time interval meet a benefit criterion, thereby assigning the placement of the data object on a basis of a data object-node-interval triplet which meets the benefit criterion;

continuing to assign additional placements of the data objects in which each placement is selected on the basis of the data object-node-interval triplet which meets the benefit criterion until a performance reaches a performance threshold; and

calculating a sum of storage costs and creation costs for the placement and the additional placements of the data objects.

18. A method of determining a lower bound for a minimum cost of placing data objects onto nodes of a distributed storage system comprising the steps of:

identifying a minimal number of non-overlapping sets which cover the nodes in the distributed storage system, each non-overlapping set comprising an effective node;

for each data object, performing the steps of;

for each effective node, determining a candidate time interval for placing the data object onto the effective node that meets a first benefit criterion;

while a performance threshold exceeds a performance, iteratively performing the steps of;

assigning a placement of the data object onto the effective node for the candidate time interval which meets a second benefit criterion, thereby reducing non-placement time intervals for the effective node by the candidate time interval; and

determining a new candidate time interval for the effective node selected from the non-placement time intervals, the new candidate time interval meeting the first benefit criterion; and

calculating a sum of storage costs and creation costs for the placements of the data objects.

19. The method of claim 18 wherein the first benefit criterion comprises a maximum for a ratio of covered demand to a placement cost for placing the data object onto the effective node.

20. The method of claim 18 wherein the second benefit criterion comprises a maximum for a ratio of covered demand to a placement cost for placing the data object onto any of the effective nodes.

21. A computer readable memory comprising computer code for implementing a method of determining a lower bound for a minimum cost of placing data objects onto nodes of a distributed storage system, the method of determining the lower bound for the minimum cost of placing the data objects comprising the steps of:

for each data object, assigning a placement of the data object to a node and a time interval which meets a benefit criterion, thereby assigning the placement of the data object to a node-interval;

for each data object, continuing to assign additional placements of the data object to other node-intervals which each meet the benefit criterion until a performance reaches a performance threshold; and

calculating a sum of storage costs and creation costs for the placement and the additional placements of the data objects.

22. A computer readable memory comprising computer code for implementing a method of determining a lower bound for a minimum cost of placing data objects onto nodes of a distributed storage system, the method of determining the lower bound for the minimum cost of placing the data objects comprising the steps of:

assigning a placement of a data object to a node and a time interval for which the data object, the node, and the time interval meet a benefit criterion, thereby assigning the placement of a data object-node-interval triplet;

continuing to assign additional placements of the data objects in which each placement is selected on a basis of the data object-node-interval triplet which meets the benefit criterion until a performance reaches a performance threshold; and

calculating a sum of storage costs and creation costs for the placement and the additional placements of the data objects.

23. A computer readable memory comprising computer code for implementing a method of determining a lower bound for a minimum cost of placing data objects onto nodes of a distributed storage system, the method of determining the lower bound for the minimum cost of placing the data objects comprising the steps of:

identifying a minimal number of non-overlapping sets which cover the nodes in the distributed storage system, each non-overlapping set comprising an effective node;

for each data object, performing the steps of;

for each effective node, determining a candidate time interval for placing the data object onto the effective node that provides a maximum nodal benefit;

while a performance threshold exceeds a performance, iteratively performing the steps of;

assigning a placement of the data object onto the effective node for the candidate time interval which provides a maximum benefit, thereby reducing non-placement time intervals for the effective node by the candidate time interval; and

determining a new candidate time interval for the effective node selected from the non-placement time intervals, the new candidate time interval providing the maximum nodal benefit; and

calculating a sum of storage costs and creation costs for the placements of the data objects.