# US 2026/0178461 A1 · Managing operation of data processing systems using time-weighted telemetry data

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- Number: US 2026/0178461 A1
- Document ID: US20260178461A1
- Status: Published application
- Kind: A1
- Application number: 18/989,917
- Filed: 2024-12-20
- Published: 2026-06-25
- Earliest claimed: 2024-12-20
- Assignees: Dell Products L.P.
- Applicants: Dell Products L.P.
- Inventors: ASHOK NARAYANAN POTTI; TSEHSIN JASON LIU; ZIJIA WANG; DALE WANG; MIN GONG
- Web page: https://patentgrep.com/patent/US20260178461A1

## CPC

- G06F 11/3075: {the data filtering being achieved in order to maintain consistency among the monitored data, e.g. ensuring that the monitored data belong to the same timeframe, to the same system or component}
- G06F 11/3006: {where the computing system is distributed, e.g. networked systems, clusters, multiprocessor systems (multiprogramming arrangements G06F9/46; allocation of resources G06F9/50)}
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)

## Abstract

Methods and systems for managing operation of a distributed system of data processing systems are disclosed. The operation may be managed by identifying that a data processing system has drifted from a previous state based on telemetry data for the data processing system. Based on a similarity map, the data processing system may maintain a time-weighted telemetry data cache that may include telemetry data for a portion of data processing systems deemed to be similar to the data processing system. The time-weighted telemetry data cache and/or the similarity map may subsequently be updated when the data processing system is identified to have drifted. The updated time-weighted telemetry data cache may be used for detecting anomalies in the telemetry data for the data processing system.

## Claims

### Claim 1

A method for managing operation of a distributed system comprising data processing systems, the method comprising:
obtaining telemetry data for a data processing system of the data processing systems;
making a first determination regarding whether the data processing system drifted from a previous state using the telemetry data and historic telemetry data for the data processing system;
in a first instance of the first determination where the data processing system has drifted:
updating a similarity map using the telemetry data and a global time-weighted telemetry data cache for the data processing systems, the updated similarity map indicating a portion of the data processing systems as being similar to the data processing system;
updating a local time-weighted telemetry data cache for the portion of the data processing systems to obtain an updated local time-weighted telemetry data cache;
making a second determination regarding whether the telemetry data is anomalous using the updated local time-weighted telemetry data cache; and
in a first instance of the second determination where the telemetry data is anomalous:
performing a management process for the data processing system based on the telemetry data to facilitate continued provisioning of computer implemented services.

### Claim 2 (depends on 1)

The method of claim 1, further comprising:
in a second instance of the first determination where the data processing system has not drifted:
making a third determination regarding whether the telemetry data is anomalous using the local time-weighted telemetry data cache; and
in a first instance of the third determination where the telemetry data is anomalous:
performing a second management process for the data processing system based on the telemetry data to facilitate continued provisioning of the computer implemented services.

### Claim 3 (depends on 2)

The method of claim 2, wherein the local time-weighted telemetry data cache comprises telemetry data over time from at least one of the data processing systems deemed to be similar to the data processing system by the similarity map.

### Claim 4 (depends on 3)

The method of claim 3, wherein updating the similarity map comprises:
applying a weighting algorithm to the telemetry data to weight more recent telemetry data of the telemetry data over time more highly in identifying levels of similarity between the data processing system and other data processing systems of the data processing systems.

### Claim 5 (depends on 4)

The method of claim 4, wherein the weighting algorithm applies exponentially decaying weights to the telemetry data over time.

### Claim 6 (depends on 1)

The method of claim 1, wherein the similarity map quantifies levels of similarity between the data processing systems, and the portion of the data processing systems is discriminated from the data processing systems based on the levels of similarity.

### Claim 7 (depends on 6)

The method of claim 6, wherein the levels of similarity are based on, for the data processing system:
device information;
network information;
configuration information; and
workload information.

### Claim 8 (depends on 1)

The method of claim 1, wherein performing the management process comprises:
identifying a level of autonomy for selection of a manner in which to perform the management process based on an estimated impact level of a forthcoming operation of the management process.

### Claim 9 (depends on 8)

The method of claim 8, wherein the level of autonomy is identified using an autonomy model that vests more decision power in the data processing system as the estimated impact level is reduced and vests less decision power in the data processing system as the estimated impact level is increased.

### Claim 10 (depends on 8)

The method of claim 8, wherein the performing the management process further comprises:
identifying a second portion of the data processing systems using the similarity map; and
collaboratively performing, by the data processing system and the second portion of the data processing systems, the forthcoming operation in accordance with the selected manner of the management process.

### Claim 11

A non-transitory machine-readable medium having instructions stored therein, which when executed by a processor, cause the processor to perform operations for managing operation of a distributed system comprising data processing systems, the operations comprising:
obtaining telemetry data for a data processing system of the data processing systems;
making a first determination regarding whether the data processing system drifted from a previous state using the telemetry data and historic telemetry data for the data processing system;
in a first instance of the first determination where the data processing system has drifted:
updating a similarity map using the telemetry data and a global time-weighted telemetry data cache for the data processing systems, the updated similarity map indicating a portion of the data processing systems as being similar to the data processing system;
updating a local time-weighted telemetry data cache for the portion of the data processing systems to obtain an updated local time-weighted telemetry data cache;
making a second determination regarding whether the telemetry data is anomalous using the updated local time-weighted telemetry data cache; and
in a first instance of the second determination where the telemetry data is anomalous:
performing a management process for the data processing system based on the telemetry data to facilitate continued provisioning of computer implemented services.

### Claim 12 (depends on 11)

The non-transitory machine-readable medium of claim 11, further comprising:
in a second instance of the first determination where the data processing system has not drifted:
making a third determination regarding whether the telemetry data is anomalous using the local time-weighted telemetry data cache; and
in a first instance of the third determination where the telemetry data is anomalous:
performing a second management process for the data processing system based on the telemetry data to facilitate continued provisioning of the computer implemented services.

### Claim 13 (depends on 12)

The non-transitory machine-readable medium of claim 12, wherein the local time-weighted telemetry data cache comprises telemetry data over time from at least one of the data processing systems deemed to be similar to the data processing system by the similarity map.

### Claim 14 (depends on 13)

The non-transitory machine-readable medium of claim 13, wherein updating the similarity map comprises:
applying a weighting algorithm to the telemetry data to weight more recent telemetry data of the telemetry data over time more highly in identifying levels of similarity between the data processing system and other data processing systems of the data processing systems.

### Claim 15 (depends on 14)

The non-transitory machine-readable medium of claim 14, wherein the weighting algorithm applies exponentially decaying weights to the telemetry data over time.

### Claim 16

A system, comprising:
a processor; and
a memory coupled to the processor to store instructions, which when executed by the processor, cause the processor to perform operations for managing operation of a distributed system comprising data processing systems, the operations comprising:
obtaining telemetry data for a data processing system of the data processing systems;
making a first determination regarding whether the data processing system drifted from a previous state using the telemetry data and historic telemetry data for the data processing system;
in a first instance of the first determination where the data processing system has drifted:
updating a similarity map using the telemetry data and a global time-weighted telemetry data cache for the data processing systems, the updated similarity map indicating a portion of the data processing systems as being similar to the data processing system
updating a local time-weighted telemetry data cache for the portion of the data processing systems to obtain an updated local time-weighted telemetry data cache;
making a second determination regarding whether the telemetry data is anomalous using the updated local time-weighted telemetry data cache; and
in a first instance of the second determination where the telemetry data is anomalous:
performing a management process for the data processing system based on the telemetry data to facilitate continued provisioning of computer implemented services.

### Claim 17 (depends on 16)

The system of claim 16, further comprising:
in a second instance of the first determination where the data processing system has not drifted:
making a third determination regarding whether the telemetry data is anomalous using the local time-weighted telemetry data cache; and
in a first instance of the third determination where the telemetry data is anomalous:
performing a second management process for the data processing system based on the telemetry data to facilitate continued provisioning of the computer implemented services.

### Claim 18 (depends on 17)

The system of claim 17, wherein the local time-weighted telemetry data cache comprises telemetry data over time from at least one of the data processing systems deemed to be similar to the data processing system by the similarity map.

### Claim 19 (depends on 18)

The system of claim 18, wherein updating the similarity map comprises:
applying a weighting algorithm to the telemetry data to weight more recent telemetry data of the telemetry data over time more highly in identifying levels of similarity between the data processing system and other data processing systems of the data processing systems.

### Claim 20 (depends on 19)

The system of claim 19, wherein the weighting algorithm applies exponentially decaying weights to the telemetry data over time.