Microsoft had 163 patents in cloud during Q4 2023. Microsoft Corp’s Q4 2023 patents include techniques for real-time detection of metric baseline behavior change, identifying congested network links and throttling applications contributing to congestion, reducing latencies in IoT devices for anomaly detection, autoscaling virtual machine nodes with overclocking capabilities, and a method for instantiating a network service through a sequence of required resources. GlobalData’s report on Microsoft gives a 360-degreee view of the company including its patenting strategy. Buy the report here.
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Microsoft grant share with cloud as a theme is 36% in Q4 2023. Grant share is based on the ratio of number of grants to total number of patents.
Recent Patents
Application: Real time detection of metric baseline behavior change (Patent ID: US20230418700A1)
The patent filed by Microsoft Corp. describes techniques for real-time detection of metric baseline behavior change. These techniques involve generating reference and sample distance signatures based on historic and sample time series information for a component metric, comparing them to determine a signature difference, and identifying a baseline change candidate if the signature difference exceeds a distance threshold. The system includes a cloud computing platform with tenant components, where the component metric can measure activity such as request duration metrics, dependency duration metrics, or client performance metrics related to different types of clients like browsers, operating systems, or client applications.
The system further includes a training module using a one-class support vector machine (SVM) to periodically generate reference distance signatures and a sampling module to generate sample distance signatures for the component metric. The method involves generating reference and sample distance signatures, determining a signature difference, and presenting an alert notification if the second period of time is identified as a baseline change candidate. Additionally, the device described in the patent utilizes support vector machine models to generate reference and sample distance signatures, compare them to determine a signature difference, and provide an indication if the second period of time is not a baseline change candidate based on the difference being less than a distance threshold.
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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.
