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公开(公告)号:US11902150B2
公开(公告)日:2024-02-13
申请号:US17594721
申请日:2020-03-23
Applicant: Hewlett Packard Enterprise Development LP
Inventor: Duncan Roweth
IPC: H04L45/28 , H04L45/028 , H04L45/125 , H04L45/00 , H04L45/122 , H04L47/76 , H04L49/15 , H04L49/00 , H04L69/40 , H04L47/10 , H04L49/9005 , H04L47/34 , H04L67/1097 , G06F13/16 , H04L45/021 , H04L47/12 , G06F13/42 , H04L47/2441 , H04L47/30 , H04L47/62 , H04L47/24 , H04L49/90 , G06F13/38 , G06F13/40 , H04L45/745 , H04L47/2483 , H04L47/629 , H04L47/80 , H04L49/101 , H04L45/12 , H04L47/122 , G06F12/1036 , G06F15/173 , H04L43/10 , H04L45/42 , H04L47/11 , G06F12/0862 , G06F12/1045 , H04L47/32 , G06F9/54 , G06F13/14 , G06F9/50 , H04L47/22 , H04L47/52 , H04L47/6275 , H04L45/24 , H04L45/7453 , H04L45/16 , H04L69/22 , H04L47/762 , H04L47/78 , H04L47/20 , H04L49/9047 , H04L1/00 , H04L43/0876 , H04L47/2466 , H04L47/625 , H04L69/28
CPC classification number: H04L45/28 , G06F9/505 , G06F9/546 , G06F12/0862 , G06F12/1036 , G06F12/1063 , G06F13/14 , G06F13/16 , G06F13/1642 , G06F13/1673 , G06F13/1689 , G06F13/385 , G06F13/4022 , G06F13/4068 , G06F13/4221 , G06F15/17331 , H04L1/0083 , H04L43/0876 , H04L43/10 , H04L45/021 , H04L45/028 , H04L45/122 , H04L45/123 , H04L45/125 , H04L45/16 , H04L45/20 , H04L45/22 , H04L45/24 , H04L45/38 , H04L45/42 , H04L45/46 , H04L45/566 , H04L45/70 , H04L45/745 , H04L45/7453 , H04L47/11 , H04L47/12 , H04L47/122 , H04L47/18 , H04L47/20 , H04L47/22 , H04L47/24 , H04L47/2441 , H04L47/2466 , H04L47/2483 , H04L47/30 , H04L47/32 , H04L47/323 , H04L47/34 , H04L47/39 , H04L47/52 , H04L47/621 , H04L47/626 , H04L47/629 , H04L47/6235 , H04L47/6275 , H04L47/76 , H04L47/762 , H04L47/781 , H04L47/80 , H04L49/101 , H04L49/15 , H04L49/30 , H04L49/3009 , H04L49/3018 , H04L49/3027 , H04L49/90 , H04L49/9005 , H04L49/9021 , H04L49/9036 , H04L49/9047 , H04L67/1097 , H04L69/22 , H04L69/40 , G06F2212/50 , G06F2213/0026 , G06F2213/3808 , H04L69/28
Abstract: System and methods are described for providing adaptive routing in the presence of persistent flows. Switches in a fabric have the capability to establish flow channels. Switches can adaptively route flows, while monitoring transmission characteristics of the flows channels to identify whether any flows are experiencing congestion towards a destination. In response to detecting congestion, it can be further determined whether the flow is related to a source of congestion, or alternative the flow is a victim of congestion. Flows that are a source of congestion have their routing constrained to prevent congestion from propagating. For example, new packets of a flow that is a source of congestion may be forced to only take the path of the data transmission that detected said congestion (preventing congestion from spreading). Alternatively, victims of congestion do not have their routing constrained, and packets can take any path as permitted by adaptive routing.
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公开(公告)号:US11902135B2
公开(公告)日:2024-02-13
申请号:US17728955
申请日:2022-04-25
Applicant: MAGDATA INC.
Inventor: Jong Min Kim , Ho Jeong Hwang , Yun Young Hur
IPC: H04L43/0876 , H04L43/045 , H04L47/283
CPC classification number: H04L43/0876 , H04L43/045 , H04L47/283
Abstract: An aspect of the present disclosure discloses a method for diagnosing a network performance in an apparatus for diagnosing network performance connected to a switching device provided between a first entity and a second entity. The method may include: obtaining at least one mirrored packet for at least one packet transmitted between the first entity and the second entity based on mirroring from the switching device, calculating performance related indicator representing performance of a network service associated with the first entity and the second entity based on at least a part of information included in the at least one mirrored packet, and storing the calculated performance related indicators.
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公开(公告)号:US11902124B2
公开(公告)日:2024-02-13
申请号:US18058091
申请日:2022-11-22
Applicant: Cisco Technology, Inc.
Inventor: Mohammadreza Attar , Navindra Yadav , Abhishek Ranjan Singh , Vimalkumar Jeyakumar , Shashidhar Gandham , Roberto Fernando Spadaro
IPC: H04L43/045 , G06F3/0482 , G06F3/04842 , G06F3/04847 , G06F9/455 , G06F16/11 , G06F16/13 , G06F16/17 , G06F16/16 , G06F16/23 , G06F16/174 , H04L9/40 , G06N20/00 , G06F21/55 , G06F21/56 , G06F16/28 , G06F16/2457 , G06F16/248 , G06F16/29 , G06F16/9535 , G06N99/00 , H04L9/32 , H04L41/0668 , H04L43/0805 , H04L43/0811 , H04L43/0852 , H04L43/106 , H04L45/00 , H04L45/50 , H04L67/12 , H04L43/026 , H04L61/5007 , H04L67/01 , H04L67/51 , H04L67/75 , H04L67/1001 , H04W72/54 , H04L43/062 , H04L43/10 , H04L47/2441 , H04L41/0893 , H04L43/08 , H04L43/04 , H04W84/18 , H04L7/10 , H04L41/046 , H04L43/0876 , H04L41/12 , H04L41/16 , H04L41/0816 , G06F21/53 , H04L41/22 , H04L41/0803 , H04L43/0829 , H04L43/16 , H04L1/24 , H04L9/08 , H04J3/06 , H04J3/14 , H04L47/20 , H04L47/32 , H04L43/0864 , H04L47/11 , H04L69/22 , H04L45/74 , H04L47/2483 , H04L43/0882 , H04L41/0806 , H04L43/0888 , H04L43/12 , H04L47/31 , G06T11/20 , H04L43/02 , H04L47/28 , H04L69/16 , H04L45/302 , H04L67/50
CPC classification number: H04L43/045 , G06F3/0482 , G06F3/04842 , G06F3/04847 , G06F9/45558 , G06F16/122 , G06F16/137 , G06F16/162 , G06F16/17 , G06F16/173 , G06F16/174 , G06F16/1744 , G06F16/1748 , G06F16/235 , G06F16/2322 , G06F16/2365 , G06F16/248 , G06F16/24578 , G06F16/285 , G06F16/288 , G06F16/29 , G06F16/9535 , G06F21/53 , G06F21/552 , G06F21/556 , G06F21/566 , G06N20/00 , G06N99/00 , G06T11/206 , H04J3/0661 , H04J3/14 , H04L1/242 , H04L7/10 , H04L9/0866 , H04L9/3239 , H04L9/3242 , H04L41/046 , H04L41/0668 , H04L41/0803 , H04L41/0806 , H04L41/0816 , H04L41/0893 , H04L41/12 , H04L41/16 , H04L41/22 , H04L43/02 , H04L43/026 , H04L43/04 , H04L43/062 , H04L43/08 , H04L43/0805 , H04L43/0811 , H04L43/0829 , H04L43/0841 , H04L43/0858 , H04L43/0864 , H04L43/0876 , H04L43/0882 , H04L43/0888 , H04L43/10 , H04L43/106 , H04L43/12 , H04L43/16 , H04L45/306 , H04L45/38 , H04L45/46 , H04L45/507 , H04L45/66 , H04L45/74 , H04L47/11 , H04L47/20 , H04L47/2441 , H04L47/2483 , H04L47/28 , H04L47/31 , H04L47/32 , H04L61/5007 , H04L63/0227 , H04L63/0263 , H04L63/06 , H04L63/0876 , H04L63/145 , H04L63/1408 , H04L63/1416 , H04L63/1425 , H04L63/1433 , H04L63/1441 , H04L63/1458 , H04L63/1466 , H04L63/16 , H04L63/20 , H04L67/01 , H04L67/1001 , H04L67/12 , H04L67/51 , H04L67/75 , H04L69/16 , H04L69/22 , H04W72/54 , H04W84/18 , G06F2009/4557 , G06F2009/45587 , G06F2009/45591 , G06F2009/45595 , G06F2221/033 , G06F2221/2101 , G06F2221/2105 , G06F2221/2111 , G06F2221/2115 , G06F2221/2145 , H04L67/535
Abstract: Systems, methods, and computer-readable media are provided for determining a packet's round trip time (RTT) in a network. A system can receive information of a packet sent by a component of the network and further determine an expected acknowledgement (ACK) sequence number associated with the packet based upon received information of the packet. The system can receive information of a subsequent packet received by the component and determine an ACK sequence number and a receiving time of the subsequent packet. In response to determining that the ACK sequence number of the subsequent TCP packet matches the expected ACK sequence number, the system can determine a round trip time (RTT) of the packet based upon the received information of the packet and the received information of the subsequent packet.
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公开(公告)号:US11902122B2
公开(公告)日:2024-02-13
申请号:US17935771
申请日:2022-09-27
Applicant: CISCO TECHNOLOGY, INC.
Inventor: Jackson Ngoc Ki Pang , Navindra Yadav , Anubhav Gupta , Shashidhar Gandham , Supreeth Hosur Nagesh Rao , Sunil Kumar Gupta
IPC: H04L41/0668 , G06F21/56 , H04L43/08 , H04L43/0876 , H04L43/062 , H04L43/02 , H04L43/04 , H04L43/045 , H04L9/40 , G06F9/455 , G06N20/00 , G06F21/55 , G06F16/28 , G06F16/2457 , G06F16/248 , G06F16/29 , G06F16/16 , G06F16/17 , G06F16/11 , G06F16/13 , G06F16/174 , G06F16/23 , G06F16/9535 , G06N99/00 , H04L9/32 , H04L43/0805 , H04L43/0811 , H04L43/0852 , H04L43/106 , H04L45/00 , H04L45/50 , H04L67/12 , H04L43/026 , H04L61/5007 , H04L67/01 , H04L67/51 , H04L67/75 , H04L67/1001 , H04W72/54 , H04L43/10 , H04L47/2441 , H04L41/0893 , H04W84/18 , H04L67/10 , H04L41/046 , H04L41/12 , H04L41/16 , H04L41/0816 , G06F21/53 , H04L41/22 , G06F3/04842 , G06F3/04847 , H04L41/0803 , H04L43/0829 , H04L43/16 , H04L1/24 , H04L9/08 , H04J3/06 , H04J3/14 , H04L47/20 , H04L47/32 , H04L43/0864 , H04L47/11 , H04L69/22 , H04L45/74 , H04L47/2483 , H04L43/0882 , H04L41/0806 , H04L43/0888 , H04L43/12 , H04L47/31 , G06F3/0482 , G06T11/20 , H04L47/28 , H04L69/16 , H04L45/302 , H04L67/50
CPC classification number: H04L43/045 , G06F3/0482 , G06F3/04842 , G06F3/04847 , G06F9/45558 , G06F16/122 , G06F16/137 , G06F16/162 , G06F16/17 , G06F16/173 , G06F16/174 , G06F16/1744 , G06F16/1748 , G06F16/235 , G06F16/2322 , G06F16/2365 , G06F16/248 , G06F16/24578 , G06F16/285 , G06F16/288 , G06F16/29 , G06F16/9535 , G06F21/53 , G06F21/552 , G06F21/556 , G06F21/566 , G06N20/00 , G06N99/00 , G06T11/206 , H04J3/0661 , H04J3/14 , H04L1/242 , H04L9/0866 , H04L9/3239 , H04L9/3242 , H04L41/046 , H04L41/0668 , H04L41/0803 , H04L41/0806 , H04L41/0816 , H04L41/0893 , H04L41/12 , H04L41/16 , H04L41/22 , H04L43/02 , H04L43/026 , H04L43/04 , H04L43/062 , H04L43/08 , H04L43/0805 , H04L43/0811 , H04L43/0829 , H04L43/0841 , H04L43/0858 , H04L43/0864 , H04L43/0876 , H04L43/0882 , H04L43/0888 , H04L43/10 , H04L43/106 , H04L43/12 , H04L43/16 , H04L45/306 , H04L45/38 , H04L45/46 , H04L45/507 , H04L45/66 , H04L45/74 , H04L47/11 , H04L47/20 , H04L47/2441 , H04L47/2483 , H04L47/28 , H04L47/31 , H04L47/32 , H04L61/5007 , H04L63/0227 , H04L63/0263 , H04L63/06 , H04L63/0876 , H04L63/145 , H04L63/1408 , H04L63/1416 , H04L63/1425 , H04L63/1433 , H04L63/1441 , H04L63/1458 , H04L63/1466 , H04L63/16 , H04L63/20 , H04L67/01 , H04L67/10 , H04L67/1001 , H04L67/12 , H04L67/51 , H04L67/75 , H04L69/16 , H04L69/22 , H04W72/54 , H04W84/18 , G06F2009/4557 , G06F2009/45587 , G06F2009/45591 , G06F2009/45595 , G06F2221/033 , G06F2221/2101 , G06F2221/2105 , G06F2221/2111 , G06F2221/2115 , G06F2221/2145 , H04L67/535
Abstract: An approach for establishing a priority ranking for endpoints in a network. This can be useful when triaging endpoints after an endpoint becomes compromised. Ensuring that the most critical and vulnerable endpoints are triaged first can help maintain network stability and mitigate damage to endpoints in the network after an endpoint is compromised. The present technology involves determining a criticality ranking and a secondary value for a first endpoint in a datacenter. The criticality ranking and secondary value can be combined to form priority ranking for the first endpoint which can then be compared to a priority ranking for a second endpoint to determine if the first endpoint or the second endpoint should be triaged first.
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55.
公开(公告)号:US11895511B2
公开(公告)日:2024-02-06
申请号:US17195788
申请日:2021-03-09
Applicant: Plume Design, Inc.
Inventor: Nipun Agarwal , William J. McFarland , Yoseph Malkin , Na Hyun Ha , Yusuke Sakamoto , Sai Venkatraman , Sandeep Eyyuni , Rohit Thadani , Adam Hotchkiss
IPC: H04W24/02 , H04L43/0876 , H04L41/0253 , H04L41/12 , H04L41/14 , H04L43/045 , H04L41/22 , H04W84/12 , H04L41/147 , H04L43/0882 , H04L43/0888 , H04L43/0894
CPC classification number: H04W24/02 , H04L41/0253 , H04L41/12 , H04L41/14 , H04L41/22 , H04L43/045 , H04L43/0876 , H04L41/147 , H04L43/0882 , H04L43/0888 , H04L43/0894 , H04W84/12
Abstract: System and methods include obtaining Wi-Fi network data, over the Internet, associated with a plurality of Wi-Fi networks each Wi-Fi network having one or more access points and each Wi-Fi network being associated with a customer of one or more service providers and obtaining customer data for each customer associated with the plurality of Wi-Fi networks, the customer data including call-ins made by customers; aggregating and filtering the data; analyzing the aggregated and filtered data including correlating the call-ins made by customers to the Wi-Fi network data; predicting customer call-ins based on correlations made between the call-ins made by customers and the Wi-Fi network data; and initiating a customer outreach workflow prior to a predicted customer call-in.
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公开(公告)号:US20240036936A1
公开(公告)日:2024-02-01
申请号:US18482769
申请日:2023-10-06
Applicant: Dynavisor, Inc.
Inventor: Sreekumar Nair
IPC: G06F9/50 , G06F9/455 , G06F11/00 , H04L43/0876 , H04L67/52
CPC classification number: G06F9/5077 , G06F9/45558 , G06F11/00 , G06F9/5072 , H04L43/0876 , H04L67/52 , G06F2009/45591 , G06F2009/45562 , H04L67/10
Abstract: A system and method for providing cloud virtualization (SV) is disclosed. According to one embodiment, a system includes a transactional cloud manager and a compute cluster connected to the transactional cloud manager. The compute cluster includes a system monitor and a control manager in a host. A virtual machine runs on the host, wherein the virtual machine has a VM system monitor and a VM control manager. The transactional cloud manager creates virtual machine clusters on the host.
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公开(公告)号:US11888920B2
公开(公告)日:2024-01-30
申请号:US17611529
申请日:2020-05-15
Applicant: Canopus Networks Pty Ltd
IPC: H04L65/80 , H04L65/61 , H04L41/5067 , H04L43/0876
CPC classification number: H04L65/80 , H04L41/5067 , H04L43/0876 , H04L65/61
Abstract: Disclosed are a process and apparatus for classifying video streams of an online streaming media service in real-time. The process includes processing data packets representing one or more video streams between a service provider and a user access network, generating flow activity data from the packets representing quantitative metrics of network transport activity, and applying a trained classifier to the flow activity data to classify each of the video streams as either a live video stream or a video-on-demand (VoD) stream.
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58.
公开(公告)号:US11888718B2
公开(公告)日:2024-01-30
申请号:US17649223
申请日:2022-01-28
Applicant: Palo Alto Networks, Inc.
Inventor: Ke Tian , Yilin Zhao , Xiaoyi Duan , Jun Du
IPC: G06N20/00 , H04L9/40 , H04L43/0876
CPC classification number: H04L43/0876
Abstract: An anomalous behavior detector has been designed to detect novel behavioral changes of devices based on network traffic data that likely correlate to anomalous behaviors. The anomalous behavior detector uses the local outlier factor (LOF) algorithm with novelty detection. After initial semi-supervised training with a single class training dataset representing stable device behaviors, the obtained model continues learning frontiers that delimit subspaces of inlier observations with live network traffic data. Instead of traffic variables being used as features, the features that form feature vectors are similarities of network traffic variable values across time intervals. A feature vector for the anomalous behavior detector represents stability or similarity of network traffic variables that have been chosen as device identifiers and behavioral indicators.
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公开(公告)号:US11888714B2
公开(公告)日:2024-01-30
申请号:US17645594
申请日:2021-12-22
Applicant: Juniper Networks, Inc.
Inventor: Harshit Naresh Chitalia , Avi K. Patel , Parantap Roy , Travis Gregory Newhouse , Sumeet Singh , Neeren Shripad Patki
IPC: H04L43/045 , G06F9/50 , G06F11/34 , G06F11/30 , G06F21/41 , G06F11/32 , H04L43/06 , H04L43/0876 , G06F3/04847
CPC classification number: H04L43/045 , G06F9/5072 , G06F11/3006 , G06F11/327 , G06F11/3433 , G06F11/3452 , G06F21/41 , H04L43/06 , H04L43/0876 , G06F3/04847 , G06F2201/815 , G06F2209/508 , G06F2221/2137
Abstract: This disclosure describes techniques for monitoring, scheduling, and performance management for virtualization infrastructures within networks. In one example, a computing system includes a plurality of different cloud-based compute clusters (e.g., different cloud projects), each comprising a set of compute nodes. Policy agents execute on the compute nodes to monitor performance and usage metrics relating to resources of the compute nodes. Policy controllers within each cluster deploy policies to the policy agents and evaluate performance and usage metrics from the policy agents by application of one or more rulesets for infrastructure elements of the compute cluster. Each of the policy controllers outputs data to a multi-cluster dashboard software system indicative of a current health status for the infrastructure elements based on the evaluation of the performance and usage metrics for the cluster. The multi-cluster dashboard software system data outputs, as single user interface screen, the current health status for each of the cloud-based compute clusters.
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60.
公开(公告)号:US20240031265A1
公开(公告)日:2024-01-25
申请号:US17820328
申请日:2022-08-17
Applicant: VMware, Inc.
Inventor: Jianwei SUI , Danting LIU , Donghai HAN , Wenfeng LIU , Jianjun SHEN
IPC: H04L43/0876 , G06F9/54 , G06F9/455
CPC classification number: H04L43/0876 , G06F9/547 , G06F9/45558 , G06F2009/45595
Abstract: A system and method for capturing resource usage information in a network for namespaces in which pods operate are described herein. A data structure specifies a topology that includes a gateway and routing addresses in a network whose usage is to be captured. The data structure is provided to an API of a master node controlling the pods. A controller in the master node enforces the data structure and reports results back to the API.
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