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公开(公告)号:US20170163493A1
公开(公告)日:2017-06-08
申请号:US15327021
申请日:2014-07-30
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Inventor: Alvin AuYoung , Yadi Ma , Sujata Banerjee , Juggun Lee , Puneet Sharma , Yoshio Turner
IPC: H04L12/24 , H04L12/927 , H04L12/911
Abstract: Example implementations disclosed herein can be used to allocate network resources in a software defined network (SDN). In one example implementation, a method can include receiving a plurality of resource allocation proposals from a plurality of controller modules, instructing the controller modules to generate votes for the plurality of resource allocation proposals, and selecting one of the plurality of resource allocation proposals based on the votes to instantiate the selected resource allocation proposal in the SDN.
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公开(公告)号:US20240388541A1
公开(公告)日:2024-11-21
申请号:US18447753
申请日:2023-08-10
Applicant: Hewlett Packard Enterprise Development LP
Inventor: Jean Tourrilhes , Puneet Sharma
IPC: H04L47/625 , H04L47/12
Abstract: A system maintains a queue for storing packets, which are enqueued at a tail of the queue and dequeued at a head of the queue. The system computes a queue utilization value, based on the packets stored in the queue. The system computes an excess amount value, based on the packets stored in the queue and previously tagged as excess packets. The system receives a first packet at the tail of the queue and determines whether a difference between the queue utilization value and the excess amount value exceeds a predetermined threshold. Responsive to determining that the difference exceeds the predetermined threshold, the system tags the first packet as an excess packet. Responsive to tagging the first packet as an excess packet, the system performs an operation associated with the first packet or a second packet at the head of the queue to reduce congestion.
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公开(公告)号:US12133095B2
公开(公告)日:2024-10-29
申请号:US17503232
申请日:2021-10-15
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Inventor: Faraz Ahmed , Lianjie Cao , Puneet Sharma
CPC classification number: H04W24/02 , G06N7/01 , G06N20/00 , H04W4/50 , H04W24/10 , H04W40/12 , H04W48/18
Abstract: Systems, methods, and computer-readable media are described for employing a machine learning-based approach such as adaptive Bayesian optimization to learn over time the most optimized assignments of incoming network requests to service function chains (SFCs) created within network slices of a 5G network. An optimized SFC assignment may be an assignment that minimizes an unknown objective function for a given set of incoming network service requests. For example, an optimized SFC assignment may be one that minimizes request response time or one that maximizes throughput for one or more network service requests corresponding to one or more network service types. The optimized SFC for a network request of a given network service type may change over time based on the dynamic nature of network performance. The machine-learning based approaches described herein train a model to dynamically determine optimized SFC assignments based on the dynamically changing network conditions.
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公开(公告)号:US11983074B2
公开(公告)日:2024-05-14
申请号:US18175091
申请日:2023-02-27
Applicant: Hewlett Packard Enterprise Development LP
Inventor: Diman Zad Tootaghaj , Puneet Sharma , Faraz Ahmed , Michael Zayats
IPC: G06F11/30 , G06F9/50 , G06F11/14 , G06F18/23213 , G06F11/18
CPC classification number: G06F11/1425 , G06F9/5072 , G06F9/5077 , G06F9/5083 , G06F18/23213 , G06F11/187 , G06F2209/505 , G06F2209/508
Abstract: Example implementations relate to consensus protocols in a stretched network. According to an example, a distributed system includes continuously monitoring network performance and/or network latency among a cluster of a plurality of nodes in a distributed computer system. Leadership priority for each node is set based at least in part on the monitored network performance or network latency. Each node has a vote weight based at least in part on the leadership priority of the node. Each node's vote is biased by the node's vote weight. The node having a number of biased votes higher than a maximum possible number of votes biased by respective vote weights received by any other node in the cluster is selected as a leader node.
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85.
公开(公告)号:US11888749B2
公开(公告)日:2024-01-30
申请号:US17510232
申请日:2021-10-25
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Inventor: Jean Tourrilhes , Puneet Sharma
IPC: H04L47/215 , H04L47/2441 , H04L43/10 , H04L47/783 , H04L43/0829 , H04L47/70
CPC classification number: H04L47/215 , H04L43/0829 , H04L43/10 , H04L47/2441 , H04L47/783 , H04L47/823
Abstract: Systems and methods are provided for measuring available bandwidth available in a black box network by determining a probing rate of packet transmissions between a sender and receiver. The optimal probing rate and bandwidth estimate may be determined. Additional actions may be performed, like automatically rerouting packets and/or load balancing network traffic after the probing rate is determined.
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公开(公告)号:US11886919B2
公开(公告)日:2024-01-30
申请号:US17814895
申请日:2022-07-26
Applicant: Hewlett Packard Enterprise Development LP
Inventor: Diman Zad Tootaghaj , Anu Mercian , Vivek Adarsh , Puneet Sharma
CPC classification number: G06F9/5027 , G06F9/45558 , G06F9/547 , G06F2009/4557
Abstract: Example implementations relate to edge acceleration by offloading network dependent applications to a hardware accelerator. According to one embodiment, queries are received at a cluster of a container orchestration platform. The cluster includes a host system and a hardware accelerator, each serving as individual worker machines of the cluster. The cluster further includes multiple worker nodes and a master node executing on the host system or the hardware accelerator. A first worker node executes on the hardware accelerator and runs a first instance of an application. A distribution of the queries is determined among the worker machines based on a queuing model that takes into consideration the respective compute capacities of the worker machines. Responsive to receipt of the queries by the host system or the hardware accelerator, the queries are directed to the master node or one of the worker nodes in accordance with the distribution.
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87.
公开(公告)号:US11797340B2
公开(公告)日:2023-10-24
申请号:US16874479
申请日:2020-05-14
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Inventor: Lianjie Cao , Faraz Ahmed , Puneet Sharma
IPC: G06F9/50 , G06F9/30 , G06N20/00 , G06F11/34 , G06F18/214 , G06F18/2415
CPC classification number: G06F9/5005 , G06F9/3009 , G06F9/505 , G06F9/5011 , G06F11/3409 , G06F18/214 , G06F18/24155 , G06N20/00
Abstract: Systems and methods are provided for optimally allocating resources used to perform multiple tasks/jobs, e.g., machine learning training jobs. The possible resource configurations or candidates that can be used to perform such jobs are generated. A first batch of training jobs can be randomly selected and run using one of the possible resource configuration candidates. Subsequent batches of training jobs may be performed using other resource configuration candidates that have been selected using an optimization process, e.g., Bayesian optimization. Upon reaching a stopping criterion, the resource configuration resulting in a desired optimization metric, e.g., fastest job completion time can be selected and used to execute the remaining training jobs.
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公开(公告)号:US20230275848A1
公开(公告)日:2023-08-31
申请号:US18311430
申请日:2023-05-03
Applicant: Hewlett Packard Enterprise Development LP
Inventor: Ali Tariq , Lianjie Cao , Faraz Ahmed , Puneet Sharma
IPC: H04L47/80 , H04L47/78 , H04L43/16 , H04L47/70 , H04L43/0882 , H04L47/762
CPC classification number: H04L47/803 , H04L47/781 , H04L43/16 , H04L47/822 , H04L43/0882 , H04L47/762
Abstract: Systems and methods are provided for updating resource allocation in a distributed network. For example, the method may comprise allocating a plurality of resource containers in a distributed network in accordance with a first distributed resource configuration. Upon determining that a processing workload value exceeds a stabilization threshold of the distributed network, determining a resource efficiency value of the plurality of resource containers in the distributed network. When a resource efficiency value is greater than or equal to the threshold resource efficiency value, the method may generate a second distributed resource configuration that includes a resource upscaling process, or when the resource efficiency value is less than the threshold resource efficiency value, the method may generate the second distributed resource configuration that includes a resource outscaling process. The resource allocation may transmit the second to update the resource allocation.
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公开(公告)号:US11658986B2
公开(公告)日:2023-05-23
申请号:US17123342
申请日:2020-12-16
Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP
Inventor: Puneet Sharma , Anand Mudgerikar
CPC classification number: H04L63/1416 , H04L9/3236 , H04L9/3242 , H04L9/3297 , H04L63/08 , H04L63/14 , H04L63/145
Abstract: An example system may comprise a first computing device comprising instructions executable by a hardware processor to: create, responsive to detecting a second computing device initially attempting to connect to a network, an unpopulated baseline profile for the second computing device; populate the baseline profile with initial processes running on the second computing device and initial system calls made by the initial processes during an initial operation time period of the second computing device; monitor, during a subsequent operation time period of the second computing device, subsequent processes running on the second computing device and subsequent system calls made by the subsequent processes; and detect an attack on the second computing device based on a comparison of the subsequent processes and the subsequent system calls to the populated baseline profile.
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公开(公告)号:US11606301B2
公开(公告)日:2023-03-14
申请号:US16392160
申请日:2019-04-23
Applicant: Hewlett Packard Enterprise Development LP
Inventor: Puneet Sharma , Huazhe Wang
IPC: H04L47/20 , H04L9/40 , H04L69/22 , H04L47/125
Abstract: Example method includes: receiving a plurality of intent-based network policies in a network, wherein each intent-based policy comprises at least a rule and an action to be performed by a network function on a network packet in response to the rule being matched; identifying a set of header address spaces comprising a plurality of addresses that match to a same set of rules and actions; creating an atomic address object representing the identified set of header address spaces; and verifying the plurality of intent-based network policies using the atomic address object.
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