公开(公告)号：US11202301B2

公开(公告)日：2021-12-14

申请号：US16424684

申请日：2019-05-29

Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

Inventor： Hardik Sanghavi ,  Mahesh Dantakale ,  Santosh Jayawadagi

IPC: H04L12/26 ,  H04W72/10 ,  H04W24/08

Abstract: A self-learning rate access prioritizer for high-priority applications in a wireless network is provided herein. The self-learning rate access prioritizer includes a method of assigning an application rate limiter for each high-priority network software application. The method further includes employing an assigned application rate limiter to determine the present bandwidth for a first high-priority network software application. Next, the method includes re-provisioning bandwidth to the first high-priority network software application in response to a ratio of a first bandwidth of the first high-priority network software application and a provisioned bandwidth for the first high-priority network software application. Furthermore, the method includes re-provisioning bandwidth from the first high-priority network software application in response to the ratio being less than a low utilization ratio assigned to the first high-priority network software application. In addition, the method includes iterating for each active high-priority network software application on a network.

公开(公告)号：US20240333684A1

公开(公告)日：2024-10-03

申请号：US18194588

申请日：2023-03-31

Applicant: Hewlett Packard Enterprise Development LP

Inventor： Mahesh M. Dantakale ,  Akhil R. Kothakota ,  Hardik Sanghavi

IPC: H04L9/40

CPC classification number: H04L63/0263 ,  H04L63/20

Abstract: A cloud-based application assurance service system and method using Deep Packet Inspection (DPI) enables Network Elements (NE) to access the cloud-based application assurance service to search a rules/signature database, without impacting latency on network-firewall decisions. Additionally, the application assurance service system distributes the associated mapping of the NE cache's latest contents to neighboring NEs, where a given user might next access the network. The system can recognize applications associated with network traffic and apply firewall rules. Further, the system tracks applications and uses this data to update NE caches periodically, such that NE caches are more likely to store the relevant application signatures in advance. Moreover, a historical user usage matrix is generated to track application use per user, which is used to detect a highly probable user path and transfer mapping to an associated NE.

公开(公告)号：US20200383121A1

公开(公告)日：2020-12-03

申请号：US16424684

申请日：2019-05-29

Applicant: HEWLETT PACKARD ENTERPRISE DEVELOPMENT LP

Inventor： Hardik Sanghavi ,  Mahesh Dantakale ,  Santosh Jayawadagi

IPC: H04W72/10 ,  H04L12/26 ,  H04W24/08

Abstract: A self-learning rate access prioritizer for high-priority applications in a wireless network is provided herein. The self-learning rate access prioritizer includes a method of assigning an application rate limiter for each high-priority network software application. The method further includes employing an assigned application rate limiter to determine the present bandwidth for a first high-priority network software application. Next, the method includes re-provisioning bandwidth to the first high-priority network software application in response to a ratio of a first bandwidth of the first high-priority network software application and a provisioned bandwidth for the first high-priority network software application. Furthermore, the method includes re-provisioning bandwidth from the first high-priority network software application in response to the ratio being less than a low utilization ratio assigned to the first high-priority network software application. In addition, the method includes iterating for each active high-priority network software application on a network.