-
公开(公告)号：US11568014B2
公开(公告)日：2023-01-31
申请号：US16457686
申请日：2019-06-28
Applicant: Intel Corporation
Inventor： Maria Ramirez Loaiza , S. M. Iftekharul Alam , Gabriel Arrobo Vidal , Ned M. Smith , Satish Chandra Jha
IPC: G06F16/9538 , G06F16/242 , H04L67/1097 , H04L67/568
Abstract: Systems and techniques for an information centric network (ICN) distributed search with approximate cache and forwarding information lookup. For example, a search interest packet may be received. Here, the search interest packet includes search criteria and a signal indicating that it is a search interest packet. A search for content—including content in a local content store—that meets the search criteria may then be performed. Once complete, a data packet that includes the results of the search may be transmitted towards an author of the search interest packet.
-
公开(公告)号：US11296993B2
公开(公告)日：2022-04-05
申请号：US16456886
申请日：2019-06-28
Applicant: Intel Corporation
Inventor： S M Iftekharul Alam , Maria Ramirez Loaiza , Stepan Karpenko , Gabriel Arrobo Vidal , Satish Chandra Jha , Yi Zhang , Ned M. Smith , Zongrui Ding , Kuilin Clark Chen , Kathiravetpillai Sivanesan
IPC: H04L12/801 , H04L47/10 , H04L45/021 , H04L45/74
Abstract: Systems and techniques for information centric network (ICN) approximate computation caching are described herein. For example, an interest packet that includes a feature set of input data may be received. A node may then perform a search of a local data store using the feature set to determine an approximate computation result cached in the local data store. Here, the approximate computation result may be based on input data that differs from the input data named in the interest packet. The node may then return the approximate computation result to an author of the interest packet in response to the search.
-
公开(公告)号：US20210258988A1
公开(公告)日：2021-08-19
申请号：US17251117
申请日：2018-09-28
Applicant: Intel Corporation
Inventor： Ravikumar Balakrishnan , Nageen Himayat , Yiting Liao , Gabriel Arrobo Vidal , Roya Doostnejad , Vijay Sarathi Kesavan , Venkatesan Nallampatti Ekambaram , Maria Ramirez Loaiza , Vallabbajosyula S. Somayazulu , Srikathyayani Srikanteswara
Abstract: Systems and methods of using machine-learning to improve communications across different networks are described. A CIRN node identifies whether it is within range of a source and destination node in a different network using explicit information or a machine-learning classification model. A neural network is trained to avoid interference using rewards associated with reduced interference or retransmission levels in each network or improved throughput at the CIRN node. A machine-learning scheduling algorithm determines a relay mode of the CIRN node for source and destination node transmissions. The scheduling algorithm is based on the probability of successful transmission between the source and destination nodes multiplied by a collaboration score for successful transmission and the probability of unsuccessful transmission of the particular packet multiplied by a collaboration score for unsuccessful transmission.
-
公开(公告)号：US10887796B2
公开(公告)日：2021-01-05
申请号：US16224691
申请日：2018-12-18
Applicant: Intel Corporation
Abstract: Methods, apparatus, systems and articles of manufacture are disclosed provide an apparatus to allocate bandwidth between devices, the apparatus comprising a comparator to determine whether a first dataflow to a first device is below a first fair share throughput attributed to the first device; and a weight adjustor to, in response to the comparator determining that the first dataflow is below the first fair share throughput attributed to the first device adjust the first fair share throughput such that the first dataflow is closer to the first fair share throughput; and adjust a second fair share throughput attributed to a second device such that a second dataflow to the second device is closer to the second fair share throughput.
-
公开(公告)号：US10802942B2
公开(公告)日：2020-10-13
申请号：US16235959
申请日：2018-12-28
Applicant: Intel Corporation
Inventor： Mats Agerstam , Bahareh Sadeghi , Jason Martin , Jeffrey Ota , Justin Gottschlich , Marcos Carranza , Maria Ramirez Loaiza , Alexander Heinecke , Mohammad Mejbah Ul Alam , Robert Colby , Sara Baghsorkhi , Shengtian Zhou
Abstract: An apparatus includes a data interface to obtain first sensor data from a first sensor and second sensor data from a second sensor of a monitored system; a data analyzer to extract a feature based on analyzing the first and second sensor data using a model, the model trained based on historical sensor data, the model to determine the feature as a deviation between the first and second sensor data to predict a future malfunction of the monitored system; an anomaly detector to detect an anomaly in at least one of the first sensor data or the second sensor data based on the feature, the anomaly corresponding to the future malfunction of the monitored system; and a system applicator to modify operation of the monitored system based on the anomaly.
-
Patent Agency Ranking
公开(公告)号：US20190223194A1
公开(公告)日：2019-07-18
申请号：US16367870
申请日：2019-03-28
Applicant: INTEL CORPORATION
Inventor： Gabriel Arrobo Vidal , Vijay Sarathi Kesavan , Maria Ramirez Loaiza
IPC: H04W72/12 , H04N21/4363 , H04N21/647 , H04N21/262 , H04W80/02 , H04W8/24
CPC classification number: H04W72/1226 , H04N21/26216 , H04N21/43637 , H04N21/647 , H04W8/24 , H04W80/02
Abstract: For example, an apparatus may include logic and circuitry configured to cause a wireless communication device to determine at least one video quality parameter representing an estimated quality of at least one video stream to be streamed via the wireless communication device to a display device over a wireless communication medium; to determine a scheduling policy parameter based at least on the video quality parameter; and to provide the scheduling policy parameter to a Media Access Control (MAC) scheduler to schedule wireless transmission of the at least one video stream to the display device.
-
公开(公告)号：US11665777B2
公开(公告)日：2023-05-30
申请号：US17251117
申请日：2018-09-28
Applicant: Intel Corporation
Inventor： Ravikumar Balakrishnan , Nageen Himayat , Yiting Liao , Gabriel Arrobo Vidal , Roya Doostnejad , Vijay Sarathi Kesavan , Venkatesan Nallampatti Ekambaram , Maria Ramirez Loaiza , Vallabhajosyula S. Somayazulu , Srikathyayani Srikanteswara
IPC: H04W72/12 , H04W72/1263 , G06K9/62 , G06N3/08 , H04W16/14 , H04W24/02 , H04W24/10 , H04W72/0446 , H04W88/04
CPC classification number: H04W72/1263 , G06K9/6262 , G06N3/08 , H04W16/14 , H04W24/02 , H04W24/10 , H04W72/0446 , H04W72/1231 , H04W88/04
Abstract: Systems and methods of using machine-learning to improve communications across different networks are described. A CIRN node identifies whether it is within range of a source and destination node in a different network using explicit information or a machine-learning classification model. A neural network is trained to avoid interference using rewards associated with reduced interference or retransmission levels in each network or improved throughput at the CIRN node. A machine-learning scheduling algorithm determines a relay mode of the CIRN node for source and destination node transmissions. The scheduling algorithm is based on the probability of successful transmission between the source and destination nodes multiplied by a collaboration score for successful transmission and the probability of unsuccessful transmission of the particular packet multiplied by a collaboration score for unsuccessful transmission.
-
公开(公告)号：US11157384B2
公开(公告)日：2021-10-26
申请号：US16455358
申请日：2019-06-27
Applicant: Intel Corporation
Inventor： Marcos Carranza , Mats Agerstam , Justin Gottschlich , Alexander Heinecke , Cesar Martinez-Spessot , Maria Ramirez Loaiza , Mohammad Mejbah Ul Alam , Shengtian Zhou
Abstract: Methods, apparatus, systems and articles of manufacture are disclosed for code review assistance for dynamically typed languages. An example apparatus to analyze a segment of code includes a function identifier to identify a first input of a first function call included in the segment of the code, a parameter type vector (PTV) estimator model to estimate a first data structure based on the first input, the PTV estimator model generated via a set of reviewed code, a PTV determiner to generate a second data structure based on a data parameter type of the first input, an error comparator to determine a first reconstruction error based on the first data structure, and the second data structure and a recommendation generator to, if the first reconstruction error does not satisfy a recommendation threshold, generate a first recommendation to review the first function call.
-
公开(公告)号：US20200305042A1
公开(公告)日：2020-09-24
申请号：US16456743
申请日：2019-06-28
Applicant: Intel Corporation
Inventor： S. M. Iftekharul Alam , Gabriel Arrobo Vidal , Ravikumar Balakrishnan , Kuilin Clark Chen , Zongrui Ding , Venkatesan Nallampatti Ekambaram , Maruti Gupta Hyde , Satish Chandra Jha , Stepan Karpenko , Kathiravetpillai Sivanesan , Maria Ramirez Loaiza , Ned M. Smith , Srikathyayani Srikanteswara , Yi Zhang
Abstract: To address technical problems facing producer and consumer mobility in cellular ICN/NDN networks, a technical solution includes leveraging device tracking during handover in the cellular system to optimize cache replacement and route updates during handover. This solution also improves performance by advance caching and route update during mobility handling, which reduces or eliminates interest packet flooding and latency for upcoming potential content request and retrieval. This solution also improves performance by operating based on the observed popularity of the content, and based on the mobility patterns of the consumer and producer.
-
公开(公告)号：US20190138423A1
公开(公告)日：2019-05-09
申请号：US16235959
申请日：2018-12-28
Applicant: Intel Corporation
Inventor： Mats Agerstam , Bahareh Sadeghi , Jason Martin , Jeffrey Ota , Justin Gottschlich , Marcos Carranza , Maria Ramirez Loaiza , Alexander Heinecke , Mohammad Mejbah Ul Alam , Robert Colby , Sara Baghsorkhi , Shengtian Zhou
Abstract: An apparatus includes a data interface to obtain first sensor data from a first sensor and second sensor data from a second sensor of a monitored system; a data analyzer to extract a feature based on analyzing the first and second sensor data using a model, the model trained based on historical sensor data, the model to determine the feature as a deviation between the first and second sensor data to predict a future malfunction of the monitored system; an anomaly detector to detect an anomaly in at least one of the first sensor data or the second sensor data based on the feature, the anomaly corresponding to the future malfunction of the monitored system; and a system applicator to modify operation of the monitored system based on the anomaly.
-
-
-
-
-
-
-
-
-
Search Results
20
records
(took 0.021 seconds)
