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기록

SYSTEM AND METHOD FOR CLOUD-BASED ANOMALY DETECTION AND ALERTING FOR STREAMING DATA

발명심사 중
2조회수
20청구항 · 3 독립항
§ Ⅰ

개요

발명자

Rajat Malik; Tamraparni Dasu; Yaron Kanza; Divesh Srivastava; Eleftherios Koutsofios; Gordon Woodhull

IPC 분류

G6F 9/455

CPC 분류

G6F9/45558G6F2009/4557G6F2009/45595

Aspects of the subject disclosure may include, for example, detecting data streams by a processing system including a processor, wherein the processing system is associated with an anomaly detection and alerting system in which stream processing and model maintenance is decoupled from one another, and wherein one or more dedicated virtual machines (VMs) store and maintain anomaly detection and alerting models, based on the detecting, causing, by the processing system, a plurality of stream-processing VMs to be instantiated for processing the data streams, and managing, by the processing system, data stream assignments for the plurality of stream-processing VMs based on monitoring of one or more conditions, wherein the plurality of stream-processing VMs process assigned data streams by executing instances of the anomaly detection and alerting models, and provide model outputs to the one or more dedicated VMs for updating of the anomaly detection and alerting models. Other embodiments are disclosed.

원문 (중국어)

Aspects of the subject disclosure may include, for example, detecting data streams by a processing system including a processor, wherein the processing system is associated with an anomaly detection and alerting system in which stream processing and model maintenance is decoupled from one another, and wherein one or more dedicated virtual machines (VMs) store and maintain anomaly detection and alerting models, based on the detecting, causing, by the processing system, a plurality of stream-processing VMs to be instantiated for processing the data streams, and managing, by the processing system, data stream assignments for the plurality of stream-processing VMs based on monitoring of one or more conditions, wherein the plurality of stream-processing VMs process assigned data streams by executing instances of the anomaly detection and alerting models, and provide model outputs to the one or more dedicated VMs for updating of the anomaly detection and alerting models. Other embodiments are disclosed.