Data gap bridging methods and systems

    公开(公告)号:US10893151B1

    公开(公告)日:2021-01-12

    申请号:US16447376

    申请日:2019-06-20

    Abstract: A computer implemented method for decreasing latency in a billing cycle, the method comprising receiving a first charging data report (CDR) including a sent data volume from a vendor and comparing the first CDR to an operator received data volume and when the first CDR does not match the operator received data volume, rejecting the first charging report. The method further comprising providing a second CDR having the operator received data volume to the vendor, receiving a charging data acceptance including a negotiated data volume from the vendor, constructing a publicly verifiable proof of charging based on the charging data acceptance, and sending the publicly verifiable proof of charging to the vendor.

    AGGREGATE INTERFACE INCLUDING MILLIMETER-WAVE INTERFACE AND WIRELESS LOCAL AREA NETWORK INTERFACE

    公开(公告)号:US20190268275A1

    公开(公告)日:2019-08-29

    申请号:US15904024

    申请日:2018-02-23

    Abstract: In some examples, a system for an aggregate interface including a mmWave interface and a WLAN interface consistent with the disclosure includes a sending device to assign a plurality of frames to the WLAN interface and the mmWave interface and send the plurality of frames in a sequence via an aggregate interface, where the aggregate interface includes the WLAN interface and the mmWave interface. Additionally, the system includes a receiving device communicatively coupled to the sending device to determine the plurality of frames is received in a different sequence than the sequence the plurality of frames is sent by the sending device and place the plurality of frames in the sequence the plurality of frames is sent by the sending device.

    Deterrence of user equipment device location tracking

    公开(公告)号:US10154369B2

    公开(公告)日:2018-12-11

    申请号:US15369508

    申请日:2016-12-05

    Abstract: Examples include deterrence of user equipment (UE) device location tracking. Some examples include a core network device of a telecommunication network having a processing resource and a machine-readable storage medium with instructions executable by the processing resource to receive a first service request message from the UE device that includes a pseudo-Globally Unique Temporary Identifier (p-GUTI), to send a paging message that includes the p-GUTI, and to receive a second service request message from the UE device that includes a new p-GUTI based on the p-GUTI of the first service request message matching the p-GUTI of the paging message.

    Systems and methods for mitigating cyberattacks

    公开(公告)号:US11770406B2

    公开(公告)日:2023-09-26

    申请号:US17183195

    申请日:2021-02-23

    CPC classification number: H04L63/1458 H04L63/0227

    Abstract: Systems and methods for mitigating cyberattacks are described herein. A computing system can detect illegitimate network traffic associated with a cyberattack in network traffic. The computing system can determine an amplification factor of the cyberattack based in part on a probability distribution of the illegitimate network traffic. The computing system can determine a filter to demotivate a generation of the illegitimate network traffic. The determined filter can reduce the amplification factor of the cyberattack. The computing system can implement the determined filter to block the illegitimate network traffic.

    High spatial reuse for mmWave Wi-Fi

    公开(公告)号:US11418247B2

    公开(公告)日:2022-08-16

    申请号:US16916240

    申请日:2020-06-30

    Abstract: Examples described herein provide method and systems for high spatial reuse for mmWave Wi-Fi. Examples may include identifying, by a network device, a plurality of millimeter-wave (mmWave) propagation paths between the network device and a set of neighboring devices including a target neighboring device, based on power delay profiles (PDPs) of beam training frames received by the network device from each of the neighboring devices using a plurality of mmWave beams, and determining, by the network device for each of neighboring devices in the set, an estimated angle of arrival (AoA) of each identified mmWave propagation path between the network device and the neighboring device, based on the PDPs of the received beam training frames from the neighboring device. Examples may include selecting, by the network device, one of the mmWave beams that maximizes a signal to interference and noise ratio (SINR) along the estimated AoA of each identified mmWave propagation path between the network device and the target neighboring device, and communicating, by the network device, with the target neighboring device using the selected mmWave beam.

    VIDEO ANNOTATION SYSTEM FOR DEEP LEARNING BASED VIDEO ANALYTICS

    公开(公告)号:US20220067381A1

    公开(公告)日:2022-03-03

    申请号:US17010795

    申请日:2020-09-02

    Abstract: A video annotation system for deep learning based video analytics and corresponding methods of use and operation are described that significantly improve the efficiency of video data frame labeling and the user experience. The video annotation system described herein may be deployed at a network edge and may support various intelligent annotation functionality including annotation tracking, adaptive video segmentation, and execution of predictive annotation algorithms. In addition, the video annotation system described herein supports team collaboration functionality in connection with large-scale labeling tasks.

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