END-TO-END HITLESS PROTECTION IN PACKET SWITCHED NETWORKS
    42.
    发明申请
    END-TO-END HITLESS PROTECTION IN PACKET SWITCHED NETWORKS 有权
    分组交换网络中的端到端无效保护

    公开(公告)号:US20150043330A1

    公开(公告)日:2015-02-12

    申请号:US14307573

    申请日:2014-06-18

    Abstract: A method and system are described for providing hitless protection in a packet switched network having source nodes and destination nodes. The method includes enabling a working path and a protecting path between the source and destination nodes. The working path is non-overlapping with respect to the protecting path. The method further includes replicating traffic in a given one of the source nodes to generate replicated traffic. The method also includes forwarding the traffic and the replicated traffic through a working path and a protecting path, respectively, from the given one of the source nodes to a particular one of the destination nodes. The method additionally includes delivering a hitless-protected service in the particular one of the destination nodes by selecting traffic packets received from either the working path or the protecting path.

    Abstract translation: 描述了一种用于在具有源节点和目的地节点的分组交换网络中提供无中断保护的方法和系统。 该方法包括启用源节点和目的节点之间的工作路径和保护路径。 工作路径与保护路径不重叠。 该方法还包括在给定的一个源节点中复制业务以生成复制业务。 该方法还包括将业务和复制的业务分别通过工作路径和保护路径转发到从给定的一个源节点到目标节点的特定一个。 该方法还包括通过选择从工作路径或保护路径接收到的业务分组来递送目标节点中的特定一个节点中的无受保护的服务。

    DOMAIN GENERALIZATION FOR CROSS-DOMAIN RAIN INTENSITY DETECTION BASED ON DISTRIBUTED FIBER OPTIC SENSING (DFOS)

    公开(公告)号:US20250130349A1

    公开(公告)日:2025-04-24

    申请号:US18901719

    申请日:2024-09-30

    Abstract: Disclosed are systems, methods, and structures that provide superior DFOS rain intensity measurements and introduce a universal solution for rain intensity detection based on the data collected by distributed acoustic sensing (DAS) technology and a designed domain generalization method. As a result, systems and methods according to the present disclosure distinguish the rain intensity of a large area through which the fiber optic cables traverse and address the domain shift issue, by employing a domain generalization technique based on machine learning technology in which newly collected target domain inference data may be distributed differently from the previously captured training source domain data. To generalize the trained model to different target domains, source domain distributions are enriched by disturbing the distribution in the frequency domain. Algorithms specifically designed to transfer the noise pattern under ambient noise environments are used to further augment the source domain distributions.

    AUTOMATIC CALIBRATION FOR BACKSCATTERING-BASED DISTRIBUTED TEMPERATURE SENSOR

    公开(公告)号:US20240302225A1

    公开(公告)日:2024-09-12

    申请号:US18598386

    申请日:2024-03-07

    CPC classification number: G01K15/005 G01K11/32

    Abstract: Disclosed are vehicle-infrastructure interaction systems and methods employing a distributed fiber optic sensing (DFOS) system operating with pre-deployed fiber-optic telecommunication cables buried alongside/proximate to highways/roadways which provide 24/7 continuous information stream of vehicle traffic at multiple sites; only require a single optical sensor cable that senses/monitors multiple locations of interest and multiple lanes of traffic; the single optical sensor cable measures multiple related information (multi-parameters) about a vehicle, including driving speed, wheelbase, number of axles, tire pressure, and others, that can be used to derive secondary information such as weight-in-motion; and overall information about a fleet of vehicles, such as traffic congestion or traffic-cargo volume. Different from merely traffic counts, our approach can provide the count grouped by vehicle-types and cargo weights. Precise measurements are facilitated by high temporal sampling rates of the distributed acoustic sensing and a dedicated peak finding algorithm for extracting the timing information reliably.

    DYNAMIC LINE RATING (DLR) OF OVERHEAD TRANSMISSION LINES

    公开(公告)号:US20240133937A1

    公开(公告)日:2024-04-25

    申请号:US18485235

    申请日:2023-10-11

    CPC classification number: G01R31/085 G01R31/088

    Abstract: Systems, methods, and structures providing dynamic line rating (DLR) for overhead transmission lines based on distributed fiber optic sensing (DFOS)/distributed temperature sensing (DTS) to determine temperature of the electrical conductors. Environmental conditions such as wind speed, wind direction, and solar radiation data, are collected from environmental sensors and an acoustic modem that convert the digital data collected from the environmental sensors into generated vibration patterns that are subsequently used to vibrationally excite a DFOS optical sensor fiber. The DFOS system monitors the optical sensor fiber and detects, measures, and decodes the vibrational excitations. An Artificial Neural Network (ANN) determines a heat transfer correlation between the temperature of the optical sensor fiber and electrical conductor(s) (core temperature).

    JOINT COMMUNICATION AND SENSING FOR FALLEN TREE LOCALIZATION ON OVERHEAD LINES

    公开(公告)号:US20240085238A1

    公开(公告)日:2024-03-14

    申请号:US18501203

    申请日:2023-11-03

    CPC classification number: G01H9/004 G01D5/35361

    Abstract: In sharp contrast to the prior art, a fallen tree detection and localization method based on distributed fiber optical sensing (DFOS) technique and physics informed machine learning is described in which DFOS leverages existing fiber cables that are conventionally installed on the bottom layer of distribution lines and used to provide high-speed communications. The DFOS collects and transmits fallen tree induced vibration data along the length of the entire overhead lines, including distribution lines and transmission lines, where there is a fiber cable deployed. The developed physics-informed neural network model processes the data and localizes the fallen tree location along the lines. The location is interpreted in at least two aspects: the fallen tree location in terms of the fiber cable length; and the exact cable location (power cable or fiber cable) that the fallen tree mechanically impacts.

    DYNAMIC INTENT-BASED NETWORK COMPUTING JOB ASSIGNMENT USING REINFORCEMENT LEARNING

    公开(公告)号:US20230376783A1

    公开(公告)日:2023-11-23

    申请号:US18319472

    申请日:2023-05-17

    CPC classification number: G06N3/092 G06N3/045

    Abstract: An advance in the art is made according to aspects of the present disclosure directed to a method that determines virtual topology design and resource allocation for dynamic intent-based computing jobs in a mobile edge computing infrastructure when client requests are dynamic. Our method according to aspects of the present disclosure is an unsupervised machine learning approach, so that there is no need for manual labeling or pre-processing in advance, while a training process and decision making is performed online. In sharp contrast to the prior art, our method according to aspects of the present disclosure utilizes reinforcement learning techniques to make an efficient assignment in which two neural networks—a policy neural network and a value neural network—are used interactively to achieve the assignment. A training process is performed through a batch (or group) processing style in an online manner.

    COLORLESS DISTRIBUTED FIBER OPTIC SENSING / DISTRIBUTED VIBRATION SENSING

    公开(公告)号:US20230152151A1

    公开(公告)日:2023-05-18

    申请号:US17987822

    申请日:2022-11-15

    CPC classification number: G01H9/004 G01D5/35361

    Abstract: Systems, methods, and structures for colorless distributed fiber optic sensing/distributed vibration sensing (DOFS/DVS) over dense wavelength division multiplexing (DWDM) telecommunications facilities that operate over a C-band wavelength range spanning from 1525 nm to 1565 nm wherein the DOFS/DVS systems exhibit suitable reconfigurability of its wavelength to match a wavelength of a desired testing channel and may advantageously provide DOFS/DVS capabilities to existing DWDM communications infrastructure as a retrofit. Colorless DFOS/DVS systems according to the present disclosure include a length of optical sensor fiber; a colorless DFOS/DVS interrogator in optical communication with the optical sensor fiber, said colorless DFOS/DVS interrogator configured to generate optical pulses, introduce the generated pulses into the length of optical sensor fiber, and receive backscattered signals from the length of the optical sensor fiber; and an intelligent analyzer configured to analyze colorless DFOS/DVS data received by the DFOS/DVS interrogator and determine from the backscattered signals, vibrational activity occurring at locations along the length of the optical sensor fiber.

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