Microsoft Technology Licensing, LLC

Affirmed Networks, Inc.

Piotr Galecki

Ajay Punreddy

Dinesh Kumar Ramasamy

Thuy Phuong Fernandes

Huanglin Xiong

Michael Anthony Brown

Haibo Qian

Fred Walter Rink

John C Sievers

Srinivasan Venkatraman

Paul Alexander

Huimin Xu

Michael Perron

Charles Crisler

Kaykhosrow Jahanian Parsi

John Elias Maroun

Liang Tian

Thuy Fernandes

Raghavan Rajagopalan

John Sievers

Systems and methods are provided for alleviating congestion of data traffic in a wireless network in a cell site. The methods determine congestion levels for respective data connections from mobile computing devices to a network through a cell tower in a cell site. The method further determines a congestion level associated with the cell site based on a weighted aggregate of varying congestion levels associated with the respective data connections in the cell site. The disclosed technology includes flow policies associated with congestion levels. The flow policies determine weights used for determining the weighted aggregate and maximum network bandwidth enforced for the respective data connections. The disclosed technology identifies data connections that consume abnormally high amount of network bandwidth and throttles with bias against data traffic associated with these data connections with heavy traffic. Through dynamically updating traffic shaping with bias, the present disclosure alleviates congestion in the cell site.

Alleviating cell congestion in wireless networks

Techniques are described for orchestrating a cohort deployment in a computing network comprising a plurality of computing nodes implementing a virtualized computing network managed by an orchestrator. The cohort deployment is managed by a deployment broker configured to coordinate the cohort deployment. The cohort deployment includes multiple deployments, where the cohort deployment comprises a parent deployment and a spawned deployment that includes a dependency on the parent deployment.

Deployment of pod cohorts

A core network can send first data transmissions to a radio access network (RAN) at a first data rate that is based at least in part on a first RAT policy associated with a first RAT used by the RAN for downlink transmissions to user equipment. The core network can obtain information indicating that the RAN is using a second RAT for the downlink transmissions to the user equipment. The core network can cause a RAT policy that is applied to the data transmissions from the core network to the RAN to be changed from the first RAT policy to a second RAT policy that is associated with the second RAT. The core network can send second data transmissions from the core network to the RAN at a second data rate that is based at least in part on the second RAT policy.

Dynamically adjusting the bandwidth of downlink transmissions based on a radio access technology used by a radio access network

Example implementations involve systems and methods for determining bandwidth savings from a rate-limiting process. A network optimization node can determine a first reference characteristic of a first portion of adaptive bit rate (ABR) media data transmitted from a first content provider to a first user equipment while rate-limiting is disabled and store in an estimation module database associated with the network optimization node, the first reference characteristic in association with the first content provider. The node can determine a first rate-limited characteristic of a second portion of the ABR media data transmitted from the first content provider to at least one of the first user equipment and a second user equipment while rate-limiting is enabled and calculate a first bandwidth savings for the first content provider associated with rate-limiting being enabled based on a difference between the first reference characteristic and the first rate-limited characteristic.

Estimating bandwidth savings for adaptive bit rate streaming

Systems and methods are described herein for adaptively transcoding media in a communications network such that computer processing resources are effectively utilized to deal with varying traffic patterns in the communications network. A computing device receives a request to transcode content and determines a first amount of tokens based on a number of CPU cores associated with the computing device, and a currently used amount of tokens. The computing device determines a second amount of tokens associated with transcoding the content and when the first amount of tokens is less than the second amount of tokens, the computing device bypasses transcoding for the content or adjusts a transcoding parameter to reduce a number of tokens associated with transcoding the content.

Adaptive content optimization

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Lexington, MA, United States of America

Piotr Galecki