IP Library › Granted Patent US 12,737,112
Granted Patent B2
US 12,737,112 · App. 18/938,502 · Granted Sep 15, 2026

Upgrade orchestration of a storage system based on namespace range gaps

Inventors: Asimuddin Kazi (Naperville, IL); Patrick Aaron Tamborski (Chicago, IL); Shikha Shree (Chicago, IL); Stephen Garward (Grayslake, IL)
Assignee: International Business Machines Corporation
G06F3/0607H04L61/3005
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 12,737,112
App. No.
18/938,502
Granted
Sep 15, 2026
Kind
B2
Abstract

Examples described herein provide a computer-implemented method that includes identifying an upgrade to be made to a storage system. The method further includes receiving, at a management device from a plurality of storage devices of the storage system, namespace information for each of the plurality of storage devices, the namespace information being shared among the plurality of storage devices. The method further includes determining, by the management device, whether a namespace gap exists based at least in part on the namespace information for each of the plurality of storage devices. The method further includes determining, by the management device, whether a namespace gap conflict exists with respect to the upgrade. The method further includes, responsive to determining that the namespace gap conflicts with the upgrade, implementing the upgrade while reducing the namespace gap conflict.

Claims (44)

1 . A computer-implemented method comprising:

identifying an upgrade to be made to a storage system, wherein the upgrade involves replacing a failed or failing drive of the storage system;

receiving, at a management device from a plurality of storage devices of the storage system, namespace information for each of the plurality of storage devices, the namespace information being shared among the plurality of storage devices;

determining, by the management device, whether a namespace gap exists based at least in part on the namespace information for each of the plurality of storage devices;

determining, by the management device, whether a namespace gap conflict exists with respect to the upgrade, wherein a namespace gap conflict is determined to exist when it is determined that the namespace gap interferes with replacing the failed or failing drive of the storage system; and

responsive to determining that the namespace gap conflicts with the upgrade, implementing the upgrade while reducing the namespace gap conflict.

2 . The computer-implemented method of claim 1 , further comprising storing, by the management device, the namespace information for each of the plurality of storage devices.

3 . The computer-implemented method of claim 2 , wherein the namespace information is stored in a database communicatively coupled to the management device.

4 . The computer-implemented method of claim 1 , wherein determining whether the namespace gap exists comprises looping over each stripe of the plurality of storage devices to identify a gap that results in a vault operating in one of read only, alert, or write only mode.

5 . The computer-implemented method of claim 1 , wherein the namespace gap is determined to exist responsive to determining that a threshold number of memory devices of one of the plurality of storage devices are unavailable.

6 . The computer-implemented method of claim 5 , wherein the threshold number of memory devices is a read threshold.

7 . The computer-implemented method of claim 5 , wherein the threshold number of memory devices is a write threshold.

8 . The computer-implemented method of claim 1 , further comprising:

determining whether implementing the upgrade results in unavailability of the storage system; and

responsive to determining that implementing the upgrade results in unavailability of the storage system, preventing additional upgrades to the storage system.

9 . A computer system comprising:

a processor set;

one or more computer-readable storage media; and

program instructions stored on the one or more computer-readable storage media to cause the processor set to perform operations comprising:

identifying an upgrade to be made to a storage system, wherein the upgrade involves replacing a failed or failing drive of the storage system;

receiving, at a management device from a plurality of storage devices of the storage system, namespace information for each of the plurality of storage devices, the namespace information being shared among the plurality of storage devices;

determining, by the management device, whether a namespace gap exists based at least in part on the namespace information for each of the plurality of storage devices;

determining, by the management device, whether a namespace gap conflict exists with respect to the upgrade, wherein a namespace gap conflict is determined to exist when it is determined that the namespace gap interferes with replacing the failed or failing drive of the storage system; and

responsive to determining that the namespace gap conflicts with the upgrade, implementing the upgrade while reducing the namespace gap conflict.

10 . The computer system of claim 9 , wherein the operations further comprise storing, by the management device, the namespace information for each of the plurality of storage devices.

11 . The computer system of claim 10 , wherein the namespace information is stored in a database communicatively coupled to the management device.

12 . The computer system of claim 9 , wherein determining whether the namespace gap exists comprises looping over each stripe of the plurality of storage devices to identify a gap that results in a vault operating in one of read only, alert, or write only mode.

13 . The computer system of claim 9 , wherein the namespace gap is determined to exist responsive to determining that a threshold number of memory devices of one of the plurality of storage devices are unavailable.

14 . The computer system of claim 13 , wherein the threshold number of memory devices is a read threshold.

15 . The computer system of claim 13 , wherein the threshold number of memory devices is a write threshold.

16 . The computer system of claim 9 , wherein the operations further comprise:

determining whether implementing the upgrade results in unavailability of the storage system; and

responsive to determining that implementing the upgrade results in unavailability of the storage system, preventing additional upgrades to the storage system.

17 . A computer program product comprising:

one or more computer-readable storage media; and

program instructions stored on the one or more computer-readable storage media to perform operations comprising:

identifying an upgrade to be made to a storage system, wherein the upgrade involves replacing a failed or failing drive of the storage system;

receiving, at a management device from a plurality of storage devices of the storage system, namespace information for each of the plurality of storage devices, the namespace information being shared among the plurality of storage devices;

determining, by the management device, whether a namespace gap exists based at least in part on the namespace information for each of the plurality of storage devices;

determining, by the management device, whether a namespace gap conflict exists with respect to the upgrade, wherein a namespace gap conflict is determined to exist when it is determined that the namespace gap interferes with replacing the failed or failing drive of the storage system; and

responsive to determining that the namespace gap conflicts with the upgrade, implementing the upgrade while reducing the namespace gap conflict.

18 . The computer program product of claim 17 , wherein the operations further comprise storing, by the management device, the namespace information for each of the plurality of storage devices.

19 . The computer program product of claim 18 , wherein the namespace information is stored in a database communicatively coupled to the management device.

20 . The computer program product of claim 17 , wherein determining whether the namespace gap exists comprises looping over each stripe of the plurality of storage devices to identify a gap that results in a vault operating in one of read only, alert, or write only mode.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 6, 2024
From: KAZI, ASIMUDDIN; TAMBORSKI, PATRICK AARON; SHREE, SHIKHA; GARWARD, STEPHEN
To: INTERNATIONAL BUSINESS MACHINES CORPORATION
Reel/Frame 069154/0237 →
Continuity (1)
Related Publication 20260126909A1 · May 7, 2026
References Cited (93)
US 5761411A · Teague et al. · 1998 [cited by applicant]
US 7584219B2 · Zybura · 2009 [cited by examiner]
US 7987167B1 · Kazar · 2011 [cited by examiner]
US 8108483B2 · Aust · 2012 [cited by examiner]
US 8151352B1 · Novitchi · 2012 [cited by applicant]
US 8447780B1 · Plantenberg · 2013 [cited by examiner]
US 9142322B2 · Baranwal et al. · 2015 [cited by applicant]
US 9171160B2 · Vincent et al. · 2015 [cited by applicant]
US 9535774B2 · Cher et al. · 2017 [cited by applicant]
US 9686293B2 · Golshan et al. · 2017 [cited by applicant]
US 10275361B2 · Ish et al. · 2019 [cited by applicant]
US 10884648B2 · Guo et al. · 2021 [cited by applicant]
US 10891068B2 · Guo et al. · 2021 [cited by applicant]
US 11226860B1 · Baptist · 2022 [cited by examiner]
US 11314442B2 · Kazi et al. · 2022 [cited by applicant]
US 11412041B2 · Tamborski et al. · 2022 [cited by applicant]
US 11588892B1 · Khadiwala et al. · 2023 [cited by applicant]
US 11973823B1 · Ghorpade et al. · 2024 [cited by applicant]
US 20070006048A1 · Zimmer et al. · 2007 [cited by applicant]
US 20110145838A1 · De et al. · 2011 [cited by applicant]
US 20130326284A1 · Losh et al. · 2013 [cited by applicant]
US 20140032962A1 · Deshpande · 2014 [cited by applicant]
US 20150074469A1 · Cher et al. · 2015 [cited by applicant]
US 20150127919A1 · Baldwin et al. · 2015 [cited by applicant]
US 20150243373A1 · Chun et al. · 2015 [cited by applicant]
US 20160019983A1 · Chung · 2016 [cited by applicant]
US 20160072889A1 · Jung · 2016 [cited by examiner]
US 20170004309A1 · Pavlyushchik et al. · 2017 [cited by applicant]
US 20170031959A1 · Zayas et al. · 2017 [cited by applicant]
US 20170090824A1 · Tamborski · 2017 [cited by applicant]
US 20170093978A1 · Cilfone et al. · 2017 [cited by applicant]
US 20180025025A1 · Davis et al. · 2018 [cited by applicant]
US 20180239697A1 · Huang et al. · 2018 [cited by applicant]
US 20180314441A1 · Suryanarayana et al. · 2018 [cited by applicant]
US 20190065524A1 · Johnson et al. · 2019 [cited by applicant]
US 20190146675A1 · Subramanian et al. · 2019 [cited by applicant]
US 20190146907A1 · Frolikov · 2019 [cited by applicant]
US 20190188589A1 · Ponnuru et al. · 2019 [cited by applicant]
US 20190278498A1 · Dedrick · 2019 [cited by applicant]
US 20190281114A1 · Cocagne · 2019 [cited by applicant]
US 20190394272A1 · Tamborski et al. · 2019 [cited by applicant]
US 20200019447A1 · Tamborski et al. · 2020 [cited by applicant]
US 20200050365A1 · Tamborski et al. · 2020 [cited by applicant]
US 20200104056A1 · Benisty et al. · 2020 [cited by applicant]
US 20200183840A1 · Johns · 2020 [cited by examiner]
US 20200192799A1 · Johns et al. · 2020 [cited by applicant]
US 20200278896A1 · Kumari et al. · 2020 [cited by applicant]
US 20200409559A1 · Sharon et al. · 2020 [cited by applicant]
US 20210173582A1 · Kazi et al. · 2021 [cited by applicant]
US 20210216227A1 · Kazi et al. · 2021 [cited by applicant]
US 20210349782A1 · Ki et al. · 2021 [cited by applicant]
US 20210367834A1 · Palavalli et al. · 2021 [cited by applicant]
US 20220236916A1 · Esaka et al. · 2022 [cited by applicant]
US 20230195577A1 · Darnell et al. · 2023 [cited by applicant]
US 20230401120A1 · Gim et al. · 2023 [cited by applicant]
US 20240220227A1 · Kerr et al. · 2024 [cited by applicant]
US 20240361939A1 · Brown et al. · 2024 [cited by applicant]
US 20240377948A1 · Zhang et al. · 2024 [cited by applicant]
US 20250077475A1 · Qi et al. · 2025 [cited by applicant]
Authors et al.: Disclosed Without Attribution, IP.com No. IPCOM000252417D, “Method and System for Classifying Memory Devices and Slices to Create Optimal Storage Decisions in Distributed Storage Network (DSN)”, Jan. 9, … [cited by applicant]
Authors et al.: Disclosed Without Attribution, IP.com No. IPCOM000263306D, “Dispersed Storage Namespace Health Based Device Prioritization and Recovery Algorithm”, Aug. 17, 2020, 7 pages. [cited by applicant]
Authors et al.: Disclosed Without Attribution, IP.com No. IPCOM000263385D, “Methodology of Hinting the NVME Host about the NVME Queues Optimized for NVME Namespace Operation”, Aug. 26, 2020, 7 pages. [cited by applicant]
Authors et al.: Seagate Technology, LLC, IP.com No. IPCOM000268073D, “Staged NVMe in a Primary/ Secondary Relationship”, Dec. 21, 2021, 4 pages. [cited by applicant]
Han et al. “ZNS+: Advanced Zoned Namespace Interface for Supporting In-Storage Zone Compaction”, Proceedings of the 15th USENIX Symposium on Operating Systems Design and Implementation, Jul. 14-16, 2021, 17 pages. [cited by applicant]
Kazi, et al. “Namespace Range-Based Memory Device Compaction,” U.S. Appl. No. 19/078,385, filed Mar. 13, 2025, 29 pages. [cited by applicant]
Kazi, et al. “Proactive Operating System Memory Unit Replacement Based on Namespace Health,” U.S. Appl. No. 18/938,516, filed Nov. 6, 2024, 24 pages. [cited by applicant]
Min et al. “eZNS: Elastic Zoned Namespace for Enhanced Performance Isolation and Device Utilization”, ACM Transactions on Storage, Jun. 6, 2024, pp. 1-41, vol. 20, Issue 3. [cited by applicant]
Tamborski, et al. “Identifying and Visualizing Namespace Range Gaps,” U.S. Appl. No. 18/938,511, filed Nov. 6, 2024, 41 pages. [cited by applicant]
Tamborski, et al. “Processing Namespace Range Information by a Global Coordinator,” U.S. Appl. No. 18/938,523, filed Nov. 6, 2024, 27 pages. [cited by applicant]
Wang David. “Application Optimization with Flexible Zone Namespace Configurations in QLC-Based SSDs”, Silicon Motion, 2023, 16 pages. [cited by applicant]
Rahi Rohit, “Object Storage”, Oct. 2019, 18 pages, https://www.oracle.com/a/ocom/docs/cloud/object-storage-100.pdf. [cited by applicant]
SNIA, “The SNIA Dictionary”, Mar. 2022, 02 pages, https://www.snia.org/sites/default/files/dictionary/SNIADictionary.pdf. [cited by applicant]
United States Non-Final Rejection dated Oct. 27, 2025, 15 pages, in U.S. Appl. No. 18/938,523. [cited by applicant]
“Intel® Optane™ DC SSD Series”, Intel, Feb. 2012, 27 pages, https://ark.intel.com/content/www/us/en/ark/products/series/213706/intel-optane-dc-ssd-series.html. [cited by applicant]
“Intel® Solid-State Drive 520 Series”, Intel, Sep. 9, 2024, 5 pages, https://www.intel.com/content/dam/www/public/us/en/documents/product-specifications/ssd-520-specification.pdf. [cited by applicant]
“SMART Attribute Details”, Kingston, 2015, 9 pages, https://media.kingston.com/support/downloads/MKP_306_SMART_attribute.pdf. [cited by applicant]
“SSD Failures: Common Causes and Main Bad Symptoms”, Multi-cloud backup Solutions, Oct. 27, 2020, 9 pages, https://www.salvagedata.com/ssd-failures-common-causes-and-main-symptom/. [cited by applicant]
“Tabular Classification”, Hugging Face, retrieved from web dated Dec. 20, 2024, 4 pages. [cited by applicant]
“What is supervised learning?”, IBM, retrieved from web dated Dec. 20, 2024, 9 pages. [cited by applicant]
Diamantopoulos et al. “WannaLaugh: A Configurable Ransomware Emulator—Learning to Mimic Malicious Storage Traces”, arXiv:2403.07540v2 [cs.CR], Jun. 12, 2024, 22 pages, https://arxiv.org/abs/2403.07540v1#. [cited by applicant]
Gagulic et al. “Ransomware Detection with Machine Learning in Storage Systems”, University of Zurich Department of Informatics (IFI) Binzmühlestrasse 14, CH-8050 Zürich, Switzerland, Feb. 13, 2023, 114 pages, https://fi… [cited by applicant]
Kruegel Christopher. “Full System Emulation: Achieving Successful Automated Dynamic Analysis of Evasive Malware”, Lastline, 2014, 7 pages. [cited by applicant]
Lucia Theo. “An Ultimate Guide to Hard Drive Problems, Solutions and Tips”, The Wayback Machine, Jan. 13, 2021, 21 pages, https://web.archive.org/web/20210122072236/https://recoverit.wondershare.com/computer-problem/com… [cited by applicant]
Rout Sidhartha Sankar. “Reliability Aware Intelligent Memory Management (RAIMM)”, Indraprastha Institute of Information Technology Delhi, New Delhi, 2014, 54 pages, https://repository.iiitd.edu.in/jspui/handle/123456789… [cited by applicant]
Sharma Natasha. “K-Means Clustering Explained”, Neptune Blog, Apr. 15, 2024, 25 pages. [cited by applicant]
Sharma Pulkit. “An Introduction to K-Means Clustering”, Machine Learning, Dec. 18, 2024, 43 pages. [cited by applicant]
Taylor et al. “Sensor-based Ransomware Detection”, Future Technologies Conference (FTC), Nov. 29-30, 2017, 8 pages, https://s2.smu.edu/~mitch/ftp_dir/pubs/ftc17.pdf. [cited by applicant]
Wijaya Cornellius Yudha. “LLMs Implementation for Tabular Classifications”, Trying out ML Tabular Classification Task with LLM, Nov. 16, 2023, 9 pages. [cited by applicant]
Zhang et al. “Towards Foundation Models for Learning on Tabular Data”, arXiv:2310.07338 [cs.LG], Oct. 11, 2023, 22 pages. [cited by applicant]
United States Non-Final Rejection dated Dec. 17, 2025, 33 pages, in U.S. Appl. No. 18/938,511. [cited by applicant]
United States Non-Final Rejection dated Oct. 2, 2025, 38 p. in U.S. Appl. No. 18/938,516. [cited by applicant]
United States Notice of Allowance dated Mar. 10, 2026, 17 pages, in U.S. Appl. No. 18/938,511. [cited by applicant]
United States Notice of Allowance dated Apr. 27, 2026, 48 pages, in U.S. Appl. No. 19/078,385. [cited by applicant]