Microsoft Technology Licensing, LLC patent applications on April 17th, 2025
Patent Applications by Microsoft Technology Licensing, LLC on April 17th, 2025
Microsoft Technology Licensing, LLC: 26 patent applications
Microsoft Technology Licensing, LLC has applied for patents in the areas of G06N10/70 (3), G06F40/30 (3), G06F40/40 (3), G06N10/40 (2), G06T11/60 (2) G06T11/60 (2), G06N10/70 (2), G02B27/0172 (1), G06N3/04 (1), H04L63/1425 (1)
With keywords such as: data, network, based, request, processor, prompt, instance, language, api, and qubits in patent application abstracts.
Patent Applications by Microsoft Technology Licensing, LLC
Inventor(s): Mervi Kaarina YLÄ-JARKKO of Hame FI for microsoft technology licensing, llc, Tuomo Antero VON LERBER of Uusimaa FI for microsoft technology licensing, llc, Lasse-Petteri LEPPANEN of Uusimaa FI for microsoft technology licensing, llc, Klaus Henrik Valtteri KALIMA of Uusimaa FI for microsoft technology licensing, llc, Pasi Petteri HEINONEN of Uusimaa FI for microsoft technology licensing, llc, Heikki Juhana HYVÄRINEN of Uusimaa FI for microsoft technology licensing, llc
IPC Code(s): G02B27/01, F21V8/00, G02B27/00, G02B27/42
CPC Code(s): G02B27/0172
Abstract: undesirable light leakage is reduced in a mixed-reality head-mounted display device using an out-coupling diffractive optical element in a waveguide combiner that is implemented using a surface relief grating (srg) having a gradient refractive index. the srg has gratings with modulated depth in which shallower gratings have a lower refractive index and deeper gratings have a higher refractive index. the lower efficiency of the shallower gratings reduces forward-propagating virtual image light leaking into the real-world environment of the hmd device while simultaneously enabling light to propagate to the deeper gratings to thereby improve virtual image uniformity over the entirety of eyebox of the combiner. the srg with gradient refractive index is alternatively fabricated using an inkjet deposition process with resin inks having different refractive indexes and subsequent nanoimprint lithography grating imprinting or physical vapor deposition by which a thickness-modulated resin layer is applied to a constant-height grating structure.
Inventor(s): Bharath RAMAKRISHNAN of Bellevue WA US for microsoft technology licensing, llc, Husam Atallah ALISSA of Redmond WA US for microsoft technology licensing, llc, Eric C. PETERSON of Woodinville WA US for microsoft technology licensing, llc, Christian L. BELADY of Mercer Island WA US for microsoft technology licensing, llc, Dennis TRIEU of Calgary CA for microsoft technology licensing, llc, Ioannis MANOUSAKIS of Redmond WA US for microsoft technology licensing, llc, Nicholas Andrew KEEHN of Kirkland WA US for microsoft technology licensing, llc, Kathryn M. OSEEN-SENDA of Seattle WA US for microsoft technology licensing, llc, Douglas Patrick KELLEY of Sammamish WA US for microsoft technology licensing, llc
IPC Code(s): G06F1/20, H05K7/20
CPC Code(s): G06F1/206
Abstract: a processor includes a first die, a second die connected to the first die with a microfluidic volume positioned between the first die and the second die, a wicking heat spreader positioned in the microfluidic volume; and a boiling enhancement surface feature positioned on at least one surface of the wicking heat spreader.
Inventor(s): Brian Scott KRABACH of Snohomish WA US for microsoft technology licensing, llc, Umesh MADAN of Bellevue WA US for microsoft technology licensing, llc, Samuel Edward SCHILLACE of Portola Valley CA US for microsoft technology licensing, llc
IPC Code(s): G06F3/0481, G06F40/20
CPC Code(s): G06F3/0481
Abstract: a computing system is provided, including processing circuitry configured to cause an interaction interface for a trained generative model to be presented, in which the interaction interface is configured to communicate a portion of a user interaction history. the processing circuitry is further configured to receive, via the interaction interface, an input for the trained generative model to generate an output. the processing circuitry is further configured to send a command to create, via the trained generative model or another trained generative model, a whiteboard based on the user interaction history and receive the created whiteboard. the processing circuitry is further configured to generate a prompt based on the whiteboard and the instruction from the user and provide the prompt to the trained generative model. the processing circuitry is further configured to receive a response from the trained generative model and output the response via the interaction interface.
Inventor(s): Benjamin John MCMORRAN of Redmond WA US for microsoft technology licensing, llc, Ion TODIREL of Bellevue WA US for microsoft technology licensing, llc, Bogdan Ionut MIHALCEA of Sammamish WA US for microsoft technology licensing, llc
IPC Code(s): G06F8/33, G06F8/75
CPC Code(s): G06F8/33
Abstract: some embodiments engineer a prompt for submission to a language model, such as a software development large language model. some embodiments ascertain a relationship between code development information and potential context. code development information includes static analysis results, project settings, development tool history or status data, and other software development data which augments training data previously embedded in the language model. some embodiments compute a prompt inclusion score of the potential context, based on at least the relationship, and use the inclusion score to determine whether to include the potential context in the language model prompt. in some scenarios, an embodiment determines where to place the context in the prompt. scoring is performed by a formula, statistical scoring model, or machine learning scoring model. some embodiments reduce context inclusion false positives and false negatives that were based on the use of embedding similarity scores alone.
Inventor(s): Rajeev Sudhakar BHOPI of Mercer Island WA US for microsoft technology licensing, llc, Yiwen ZHU of San Francisco CA US for microsoft technology licensing, llc, Helen Mary SERR of Boston MA US for microsoft technology licensing, llc, Jonah KARPMAN of San Diego CA US for microsoft technology licensing, llc, Matthew Joseph GLEESON of New York NY US for microsoft technology licensing, llc, Nicholas Kent GLAZE of Cambridge MA US for microsoft technology licensing, llc, Subramaniam Venkatraman KRISHNAN of San Jose CA US for microsoft technology licensing, llc, Irwin Hollar MCNEELY, III of Cambridge MA US for microsoft technology licensing, llc
IPC Code(s): G06F11/34, G06F8/70
CPC Code(s): G06F11/3442
Abstract: example solutions provide an artificial intelligence (ai) agent for pre-build configuration of cloud services in order to enable the initial build of a computational resource (e.g., in a cloud service) to minimize the likelihood of excessive throttling or slack. examples leverage prior-existing utilization data and project metadata to identify similar use cases. the utilization data includes capacity information and resource consumption information (e.g., throttling and slack) for prior-existing computational resources, and the project metadata includes information for hierarchically categorization, to identify similar resources. a pre-build configuration is generated for the customer's resource, which the customer may tune based upon the customer's preferences for a cost and performance balance point.
Inventor(s): Babatunde Micheal OKUTUBO of Bellevue WA US for microsoft technology licensing, llc, Maninderjit Singh PARMAR of Redmond WA US for microsoft technology licensing, llc, Edgars SEDOLS of Bellevue WA US for microsoft technology licensing, llc
IPC Code(s): G06F16/13, G06F16/27, G06F16/28
CPC Code(s): G06F16/13
Abstract: methods and systems are provided for improved access to rows of data in a distributed data system. each data row is associated with a partition. data rows are distributed in one or more files and an impure file includes data rows associated multiple partitions. a clustering set is generated from a plurality of impure files by selecting a candidate impure file based on file access activity metrics and one or more neighbor impure files. data rows of the impure files included in the clustering set are sorted according to their respective associated partitions. a set of disjoint partition range files are generated based on the sorted data rows of the impure files included in the clustering set. each file of the set of disjoint partition range files is transferred to a respective target partition.
Inventor(s): Reshmi GHOSH of Somerville MA US for microsoft technology licensing, llc, Shaily Jignesh FOZDAR of New York City NY US for microsoft technology licensing, llc, Tianyi YAO of Somerville MA US for microsoft technology licensing, llc, Huitian JIAO of Snoqualmie WA US for microsoft technology licensing, llc, H M Sajjad HOSSAIN of Everett WA US for microsoft technology licensing, llc, Jiangning CHEN of Everett WA US for microsoft technology licensing, llc, Dario Kikuchi BERNAL of Cambridge MA US for microsoft technology licensing, llc, Tianwei CHEN of Atlanta GA US for microsoft technology licensing, llc, Irene Rogan SHAFFER of Cambridge MA US for microsoft technology licensing, llc, Zhongzhong LI of Beijing CN for microsoft technology licensing, llc, Junlin WU of Beijing CN for microsoft technology licensing, llc, Dongxiao YANG of Beijing CN for microsoft technology licensing, llc, Weiwei SHI of Beijing CN for microsoft technology licensing, llc, Yuanquan HU of Beijing CN for microsoft technology licensing, llc, Genglin HUANG of Beijing CN for microsoft technology licensing, llc, Sheikh Sadid Al HASAN of Weymouth CN for microsoft technology licensing, llc
IPC Code(s): G06F16/242, G06F16/21
CPC Code(s): G06F16/2428
Abstract: a system classifies an intent based on a received prompt and identifies system-provided prompts based on the intent. the system inputs the system-provided prompts and the received prompt to a generative artificial intelligence model, wherein the generative artificial intelligence model outputs form items corresponding to the received prompt and the system-provided prompts, the form items including form prompt items and form response items. the system converts the form items into the renderable form presentable in a user interface, wherein the renderable form includes the form prompt items and the form response items.
Inventor(s): Anders Tungeland GJERDRUM of Tromso NO for microsoft technology licensing, llc, Theodoros GKOUNTOUVAS of Tromso NO for microsoft technology licensing, llc, Jan-Ove Almli KARLBERG of Tromso NO for microsoft technology licensing, llc
IPC Code(s): G06F16/2455, G06F16/2453, G06F16/248
CPC Code(s): G06F16/2455
Abstract: solutions are disclosed that enable efficient federated graph queries across multiple isolated data stores. examples leverage the connectedness of the expected data that spans the data stores by defining the entities and relationships and inferring the intent of the queries. these are used to optimize data searches in the individual data stores. examples map each of two or more variables of the input query to elements of a public schema and use the mapping to determining a storage tag (identifying a data store) for each of the variables of the input query. store-specific queries are scheduled and performed based on at least the storage tags.
Inventor(s): Urszula Stefania CHAJEWSKA of Camano Island WA US for microsoft technology licensing, llc, Harsh SHRIVASTAVA of Redmond WA US for microsoft technology licensing, llc
IPC Code(s): G06F16/332, G06F40/40
CPC Code(s): G06F16/3328
Abstract: the disclosure relates to utilizing a domain insight system for providing plain language descriptions and insights into complex data and/or sparsely populated domains using machine-learning models and large generative models. for instance, the domain insight system converts data outputs from machine-learning models in various output formats into clear, accurate, comprehensible, and straightforward results. the domain insight system achieves this by using one or more dynamic prompts that are tailored based on the data output types and report descriptors, thus improving the accuracy and efficiency of the large generative model. in particular, the domain insight system uses specialized prompts with carefully selected parameters and, in some cases, system-level meta-prompts, to generate accurate domain-based reports and explanations for a given dataset.
Inventor(s): Durgesh Nandini DAS of Hyderabad IN for microsoft technology licensing, llc, Ranganathan SRIKANTH of Redmond WA US for microsoft technology licensing, llc, Clarence WONG of Kolkata IN for microsoft technology licensing, llc
IPC Code(s): G06F16/35, G06F16/33, G06F40/284
CPC Code(s): G06F16/35
Abstract: systems and methods for describing a composition of an article of manufacture are disclosed. in one aspect, a method includes receiving article composition data for an article of manufacture that identifies a set of parts of the article, a stated composition for each part of the set of parts, and a physical quantity of the stated composition. the method further includes classifying the stated composition of each part of the set of parts into a normalized composition that includes a set of normalized chemicals. the method further includes outputting an aggregated physical quantity of each normalized chemical for the set of parts of the article. the method can include classifying a normalized composition of each part into a material category within a hierarchical taxonomy based on the set of normalized chemicals of that normalized composition and outputting an aggregated physical quantity of each material category for the parts.
Inventor(s): K. Balaji KANNADASSAN of Chennai IN for microsoft technology licensing, llc
IPC Code(s): G06F21/64
CPC Code(s): G06F21/64
Abstract: the present application relates to messaging between instances of a microservice in a decentralized architecture. a computer device hosting an instance may include a memory storing instructions to operate a microservice and a processor. the instance receives a message for the microservice from another instance of the microservice, the message including a branch of a hash tree with at least a block for a root hash of a central node, one or more blocks for intermediate nodes, and a leaf block including message content. the instance places at least the leaf block into a local hash tree based on the branch of the hash tree. the instance verifies an integrity and an order of the message based on the root hash and the location of the leaf block in the local hash tree. the instance acts on the message content in response to verifying the integrity and the order.
Inventor(s): Dimitrios Basile DIMITRIADIS of Bellevue WA US for microsoft technology licensing, llc, Vaishnavi SHRIVASTAVA of Seattle WA US for microsoft technology licensing, llc, Milad SHOKOUHI of Seattle WA US for microsoft technology licensing, llc, Robert Alexander SIM of Bellevue WA US for microsoft technology licensing, llc, Fatemehsadat MIRESHGHALLAH of San Diego CA US for microsoft technology licensing, llc
IPC Code(s): G06F40/284, G06F40/30
CPC Code(s): G06F40/284
Abstract: a personalized natural language processing system tokenizes a plurality of sets of raw text data to generate a plurality of sets of tokenized text data for the plurality of users, respectively. the tokenized text data includes a sequence of tokens corresponding to the raw text data, the tokens at least identifying distinct words or portions of words in the raw text. the system appends predetermined user-specific tokens to the sets of tokenized text data from the users, respectively. each predetermined user-specific token corresponds to one of the users. the system processes the sets of tokenized text data using the nlp model in accordance with the appended predetermined user-specific tokens to predict a personalized classification for the sets of tokenized text data from each of the users, and outputs the personalized classifications of the tokenized text data for each of the users.
Inventor(s): Jacob Daniel ANDREAS of Somerville MA US for microsoft technology licensing, llc, Kaj Alexander Nelson BOSTROM of Austin TX US for microsoft technology licensing, llc, Hao FANG of Seattle WA US for microsoft technology licensing, llc, Harsh JHAMTANI of Redmond WA US for microsoft technology licensing, llc, Jason Michael EISNER of Baltimore MD US for microsoft technology licensing, llc, Benjamin David VAN DURME of Baltimore MD US for microsoft technology licensing, llc, Patrick Aozhe XIA of Bellevue WA US for microsoft technology licensing, llc, Eui Chul SHIN of San Francisco CA US for microsoft technology licensing, llc, Samuel McIntire THOMSON of Berkeley CA US for microsoft technology licensing, llc
IPC Code(s): G06F40/30, G06F40/205
CPC Code(s): G06F40/30
Abstract: implementations of semantic parsing using pre-trained language models are provided. one aspect includes a computing system for semantic parsing of natural language. the computing system comprises processing circuitry and memory containing instructions that, when executed, cause the processing circuitry to receive a request comprising a natural language utterance and generate a formal meaning representation using the natural language utterance and a language model comprising a semantic parser that has been prompted with training data generated by providing a dataset comprising a set of unlabeled programmatic scripts and a seed programmatic script, generating a set of parsed natural language descriptions by inputting the set of unlabeled programmatic scripts into an inverse semantic parser, generating a set of re-parsed programmatic scripts by inputting the set of parsed natural language descriptions into the semantic parser, and determining a set of labeled programmatic scripts by validating the set of re-parsed programmatic scripts.
Inventor(s): Mohamed Abdelrhman Mostafa Ali EFEKI of Kirkland WA US for microsoft technology licensing, llc, Paulo Ricardo DOS SANTOS MENDONCA of Seattle WA US for microsoft technology licensing, llc, Benjamin Eliot LUNDELL of Seattle WA US for microsoft technology licensing, llc, Xiaoyan HU of Redmond WA US for microsoft technology licensing, llc
IPC Code(s): G06N3/04
CPC Code(s): G06N3/04
Abstract: a technique is described herein for receiving a selected set of weights and a mask produced by any type of sparsification process by operating on an original set of weights. the mask describes positions of the selected set of weights and a non-selected set of weights among a combined set of weights. for example, the non-selected set of weights represent weights that have been zeroed out in the original set of weights. in an inference stage, a processor directly performs computations on the selected set of weights and the mask, without the preliminary step of reconstituting the non-selected weights in memory. instead, the processor performs computations that take into account the influence of the non-selected weights. the technique is efficient because it reduces the consumption of memory during the execution of the machine-trained model, and reduces the transactional costs associated with moving weights between memory and processing functionality.
Inventor(s): Parsa BONDERSON of Santa Barbara CA US for microsoft technology licensing, llc, David Alexander AASEN of Santa Barbara CA US for microsoft technology licensing, llc, Anna Linnea GRAENS SAMUELSSON of Goleta CA US for microsoft technology licensing, llc, Christina Paulsen KNAPP of Goleta CA US for microsoft technology licensing, llc, Marcus Palmer da SILVA of Redmond WA US for microsoft technology licensing, llc, Bradley Curtis LACKEY of Redmond WA US for microsoft technology licensing, llc
IPC Code(s): G06N10/40, G06N10/20, G06N10/70
CPC Code(s): G06N10/40
Abstract: a method for enacting a measurement circuit of a surface code on a plaquette of qubits of a qubit lattice comprises: (a) distributing among a sequence of time steps a set of one-qubit projective measurements on each of three auxiliary qubits of the plaquette; (b) distributing among the sequence of time steps a set of two-qubit projective measurements on each of four data qubits of the plaquette together with one of the three auxiliary qubits; (c) distributing among the sequence of time steps a set of two-qubit projective measurements on two or more auxiliary-qubit pairs selected from the three auxiliary qubits of the plaquette; and (d) advancing through each of the time steps of the sequence, executing the one- and two-qubit projective measurements distributed therein. in this method the measurement circuit corresponds to a stabilizer of the surface code, and the measurements generate measurement of a stabilizer operator.
Inventor(s): Parsa BONDERSON of Santa Barbara CA US for microsoft technology licensing, llc, David Alexander AASEN of Santa Barbara CA US for microsoft technology licensing, llc
IPC Code(s): G06N10/70, G06N10/20
CPC Code(s): G06N10/70
Abstract: a computing system including a processor configured to receive an indication of one or more dead data qubits and one or more dead auxiliary qubits among qubits included in a quantum computing device. the qubits are arranged in a lattice that includes plaquettes. each of the plaquettes includes data qubits and auxiliary qubits. the processor is further configured to compute a reduced lattice by, for each of the plaquettes that includes at least one dead data qubit, computing a respective first reduced plaquette that omits the dead data qubit. for each of the plaquettes that includes at least one dead auxiliary qubit, the processor is further configured to compute the reduced lattice at least in part by computing a respective second reduced plaquette that omits the dead auxiliary qubit. the processor is further configured to output instructions to implement an error correction code on the reduced lattice.
Inventor(s): Parsa BONDERSON of Santa Barbara CA US for microsoft technology licensing, llc, David Alexander AASEN of Santa Barbara CA US for microsoft technology licensing, llc, Christina Paulsen KNAPP of Goleta CA US for microsoft technology licensing, llc
IPC Code(s): G06N10/70, B82Y10/00, G06N10/40
CPC Code(s): G06N10/70
Abstract: a method for implementing a measurement circuit of a surface code on a plaquette of qubits of a majorana-tetron lattice comprises: (a) distributing among a sequence of time steps a set of one-qubit projective-measurement loops on each of three auxiliary qubits of the plaquette; (b) distributing among the sequence of time steps a set of two-qubit projective-measurement loops on each of four data qubit of the plaquette together with one of the three auxiliary qubits; (c) distributing among the sequence of time steps a set of two-qubit projective measurement loops on two or more auxiliary-qubit pairs selected from the three auxiliary qubits of the plaquette; and (d) advancing through each of the time steps of the sequence, executing the one- and two-qubit projective measurements distributed therein. in this method the measurement circuit corresponds to a stabilizer of the surface code, and the measurements generate measurement of a stabilizer operator.
Inventor(s): Sumithra BHAKTHAVATSALAM of Kirkland WA US for microsoft technology licensing, llc, Gaurav Vinayak TENDOLKAR of Reston VA US for microsoft technology licensing, llc
IPC Code(s): G06T11/60, G06F40/30, G06F40/40, G06V30/19
CPC Code(s): G06T11/60
Abstract: a device includes a processor, and a memory storing executable instructions which, when executed by the processor, cause the processor alone or in combination with other processors to perform the following functions: receive textual user input from a user describing a design to be generated; implement a first prompt generator to generate a first prompt for a large language model (llm) to restructure the user input; and implement a second prompt generator to generate a second prompt for a text-to-image model using output of the llm to produce, the second prompt to prompt the text-to-image model to produce a proposed design based on the user input. the proposed design is provided to the user via an application comprising controls for further editing the proposed design.
Inventor(s): Mingxi CHENG of Los Angeles CA US for microsoft technology licensing, llc, Ji LI of San Jose CA US for microsoft technology licensing, llc, Sumithra BHAKTHAVATSALAM of Kirkland WA US for microsoft technology licensing, llc
IPC Code(s): G06T11/60, G06F40/40, G06T5/00, G06V30/148, G06V30/19
CPC Code(s): G06T11/60
Abstract: a data processing system includes a processor, and a memory storing executable instructions which, when executed by the processor, cause the processor alone or in combination with other processors to perform the following functions: based on a list of design purposes, generate prompts requesting a large language model (llm) to produce corresponding prompts for input to a text-to-image model to generate a proposed design corresponding to each design purpose; submit the prompts from the llm to the text-to-image model; receive the proposed designs from the text-to-image model; and increase a design template library by adding a design based on the proposed designs output by the text-to-image model.
Inventor(s): Gilad PUNDAK of Rehovot IL for microsoft technology licensing, llc, Daniel SPIVAK of Ness Ziona IL for microsoft technology licensing, llc, Eran ARBEL of Netanya IL for microsoft technology licensing, llc
IPC Code(s): G09G5/10, G06T7/11, G06T7/174, H04N9/78
CPC Code(s): G09G5/10
Abstract: a system is provided comprising a display, a first processor, a second processor, an image sensor, and an ambient light sensor. on condition that the image sensor is not in use by an application, image sensor data is blocked from the first processor and routed to the second processor, to thereby enable the second processor to execute a color adjustment algorithm configured to use at least the image sensor data and ambient light data to adjust one or more color parameters of content displayed on the display, and to execute a brightness adjustment algorithm configured to use at least the image sensor data and the ambient light data to adjust a luminance of the display.
Inventor(s): John Wan Yeung SUN of Redmond WA US for microsoft technology licensing, llc, Ashok NANDOORI of Frisco TX US for microsoft technology licensing, llc, Adithya GUNDMI GUNDMI RAMESH of Issaquah WA US for microsoft technology licensing, llc, Abhishek Kumar TIWARI of Woodinville WA US for microsoft technology licensing, llc
IPC Code(s): H04L9/32, H04L45/302, H04L47/20
CPC Code(s): H04L9/32
Abstract: enforcement of a communication policy at a communication intermediary configured to communicate between a first communicating entity and a second communicating entity is provided. the communication intermediary includes packet routers. the enforcement includes identifying, by the packet routers of the communication intermediary, a secure plaintext label in each network packet of labeled network traffic received at the packet routers, evaluating whether the labeled network traffic satisfies an enforcement condition of the communication policy based on the secure plaintext label, instructing a network controller to operate on the labeled network traffic according to the communication policy, based on the operation of evaluating. each network packet includes encrypted content configured to be inaccessible by the packet routers. the secure plaintext label is accessible by the packet routers and includes a data encoding of a portion of the encrypted content.
Inventor(s): Anthony Brian HAYWARD of Edinburgh GB for microsoft technology licensing, llc, Andrew John TYLEE of Royal Leamington Spa GB for microsoft technology licensing, llc, Matthew John RUSSELL of Cambridge GB for microsoft technology licensing, llc, William Richard OULDRIDGE of Cambridge GB for microsoft technology licensing, llc, Michael Jeffrey EVANS of Harpenden GB for microsoft technology licensing, llc, Yuval KRAMER of Cambridge GB for microsoft technology licensing, llc, David Alexander JACKSON of Cambridge GB for microsoft technology licensing, llc
IPC Code(s): H04L45/28, H04L45/00, H04L45/64
CPC Code(s): H04L45/28
Abstract: high availability network services are provided in a communications network comprising a plurality of network devices including a network function implemented as two instances configured as an active instance and a backup instance. the backup instance maintains state data such that the backup instance can actively provide services in response to a failure of the active instance. a pool of data forwarding functions sends, over a tunnel connection, ingress data packets to the network function based on a mac address of the active instance on an overlay network. when the active instance has failed, the backup instance provides the network function and the pool of data forwarding functions sends over the tunnel connection, subsequent ingress data packets to the network function based on an overlay network mac address of the backup instance.
Inventor(s): Pankaj GARG of Union City CA US for microsoft technology licensing, llc, Jamie Dorea GAUDETTE of Kirkland WA US for microsoft technology licensing, llc, Luis IRUN-BRIZ of Sammamish WA US for microsoft technology licensing, llc
IPC Code(s): H04L47/267, H04L41/0659, H04L41/0663
CPC Code(s): H04L47/267
Abstract: a system for establishing network reliability for a computer network includes a plurality of initiating nodes to transmit a plurality of packets across the network and a plurality of receiving nodes to receive the plurality of packets via the network. a portion of the plurality of packets transmitted from the initiating nodes are appended with identifiers that correspond to characteristics of entities using the network. the plurality of receiving nodes transmit acknowledgement receipts associated with packets appended with the identifiers to a network monitoring system that monitors quality of service associated with the characteristics.
Inventor(s): Rachel LEMBERG of Herzliya IL for microsoft technology licensing, llc, Raphael FETTAYA of Herzliya IL for microsoft technology licensing, llc, Mohamad SALAMAH of Herzliya IL for microsoft technology licensing, llc, Yaniv LAVI of Herzliya IL for microsoft technology licensing, llc
IPC Code(s): H04L47/83, H04L47/10, H04L47/125, H04L47/762, H04L47/78
CPC Code(s): H04L47/83
Abstract: example aspects include techniques for implementing resource governance in multi-tenant environment. these techniques may include receiving a service request for a multi-tenant service from a client device, and predicting a resource utilization value (ruv) resulting from execution of the service request based on text of the service request, an amount of data associated with the client device at the multi-tenant service, and/or a temporal execution value. in addition, the techniques may include determining that the ruv is greater than a preconfigured threshold identifying an expensive request, and applying a load balancing strategy to the service request based on the ruv being greater than the preconfigured threshold.
Inventor(s): Karthik UTHAMAN of Seattle WA US for microsoft technology licensing, llc, Ashok Kumar NANDOORI of Frisco TX US for microsoft technology licensing, llc
IPC Code(s): H04L9/40
CPC Code(s): H04L63/1425
Abstract: control of network traffic in a network is provided, including classifying a network request from a network source address using request classifiers selected from a plurality of request classifiers based on the network request satisfying classification conditions of the selected request classifiers, associating the network request with each classifier metric corresponding to the selected request classifiers, aggregating the classifier metrics associated with the network request to determine an aggregate request control metric of the network request, and instructing a network traffic controller to operate on the network request based on whether the aggregate request control metric satisfies a request control condition. each of the plurality of request classifiers is associated in memory with a corresponding classifier metric.
Inventor(s): Sébastien LEVERT of Montreal CA for microsoft technology licensing, llc, Waldemar MASTYKARZ of Alphen aan den Rijn NL for microsoft technology licensing, llc, Garry James TRINDER of Goole GB for microsoft technology licensing, llc, Gavin Douglas BARRON of Bothell WA US for microsoft technology licensing, llc
IPC Code(s): H04L67/56, G06F9/54
CPC Code(s): H04L67/56
Abstract: an application programming interface (api) proxy intercepts api calls and responses for an application under test in a development environment, simulating (e.g., mocking) rate limiting and throttling behavior, which is otherwise challenging to test. the api proxy receives a api call and, based on a resource limiting parameter (e.g., rate-limiting or otherwise throttling), determines that the api call should be forwarded to the api endpoint. when the api proxy receives another api call from the application, destined for the same api endpoint, the api proxy determines to not forward the second api call, based on the resource limiting parameter (e.g., too soon after the first api call, or requests too much of a computational burden, such as exceeding a resource quota). the api proxy instead returns a throttling response, as would be expected from the api endpoint. the api proxy provides guidance messages for both outgoing calls and incoming responses.
Microsoft Technology Licensing, LLC patent applications on April 17th, 2025
- Microsoft Technology Licensing, LLC
- G02B27/01
- F21V8/00
- G02B27/00
- G02B27/42
- CPC G02B27/0172
- Microsoft technology licensing, llc
- G06F1/20
- H05K7/20
- CPC G06F1/206
- G06F3/0481
- G06F40/20
- CPC G06F3/0481
- G06F8/33
- G06F8/75
- CPC G06F8/33
- G06F11/34
- G06F8/70
- CPC G06F11/3442
- G06F16/13
- G06F16/27
- G06F16/28
- CPC G06F16/13
- G06F16/242
- G06F16/21
- CPC G06F16/2428
- G06F16/2455
- G06F16/2453
- G06F16/248
- CPC G06F16/2455
- G06F16/332
- G06F40/40
- CPC G06F16/3328
- G06F16/35
- G06F16/33
- G06F40/284
- CPC G06F16/35
- G06F21/64
- CPC G06F21/64
- G06F40/30
- CPC G06F40/284
- G06F40/205
- CPC G06F40/30
- G06N3/04
- CPC G06N3/04
- G06N10/40
- G06N10/20
- G06N10/70
- CPC G06N10/40
- CPC G06N10/70
- B82Y10/00
- G06T11/60
- G06V30/19
- CPC G06T11/60
- G06T5/00
- G06V30/148
- G09G5/10
- G06T7/11
- G06T7/174
- H04N9/78
- CPC G09G5/10
- H04L9/32
- H04L45/302
- H04L47/20
- CPC H04L9/32
- H04L45/28
- H04L45/00
- H04L45/64
- CPC H04L45/28
- H04L47/267
- H04L41/0659
- H04L41/0663
- CPC H04L47/267
- H04L47/83
- H04L47/10
- H04L47/125
- H04L47/762
- H04L47/78
- CPC H04L47/83
- H04L9/40
- CPC H04L63/1425
- H04L67/56
- G06F9/54
- CPC H04L67/56
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