Cable Television Laboratories, Inc.

Hewlett Packard Enterprise Development LP

Emc IP Holding Company LLC

Hewlett-packard Development Company, L.p.

Thomas E Sandholm

Bernardo A Huberman

Lin Cheng

Julio Lopez

Anupriya Ankolekar

Luis Alberto Campos

Sayandev Mukherjee

Niraj Tolia

Vaibhav Kamra

Dilip N Simha

Belal Hamzeh

David Penkler

W Alex Vorbau

Deny Joao Correa Azzolin

Francois-Xavier Kowalski

Jose Diego Ferreira Martins

The present disclosure generally relates to apparatus, software and methods for managing multi-channel network traffic to alleviate congestion, improve service quality and make efficient use of channel capacity. The disclosed apparatus, software and methods alleviate congestion and improve service quality by minimizing variance within a channel and/or increase overall traffic flow by minimizing the variance between channels. One or both of these objectives can be accomplished using modern portfolio theory to optimize at least one network usage parameter based on the mean and variance of the parameter(s).

Methods for managing multi-channel network traffic

An artificial intelligence network operator (aiNO) that autonomously and dynamically acquires network resources on an open marketplace includes software running a machine learning model and a processor that controls backhaul connectivity and a network communication component. In some embodiments, the aiNO facilitates resale of the acquired network resource to end users.

AiNO: an AI network operator

Agents, operating on user equipment, and related systems and methods for machine-learning aided autonomous control of mobile network access are disclosed. The agents, systems and methods allow for mobile network resources, which are pre-purchased or purchased in real-time, to be optimized according to a reward function that maximizes quality of experience as a function of price. Mobile network resources purchased in real-time may include spectrum bandwidth sold or auctioned in increments and purchased by UEs as needed.

User agents, systems and methods for machine-learning aided autonomous mobile network access

A method for dynamic allocation of communication resources includes (1) determining a risk-return characterization of a plurality of communication resource allocations across a plurality of communication channels in a communication system, (2) selecting a first allocation of the plurality of communication resource allocations from the risk-return characterization according to at least one predetermined criterion, and (3) automatically allocating communication resources among the plurality of communication channels according to the first allocation.

Methods, devices, and systems for dynamic allocation of communication resources

Systems and methods for deduplicating data are provided. An index used in deduplicating data is distributed to clients. The clients can use the distributed index to provide hints as to whether the data is deduplicated at the server. The server may be associated with a main index used to confirm whether the data is deduplicated based on the hints.

Distributed client side deduplication index cache

A novel method that dynamically changes the contention window of access points based on system load to improve performance in a dense Wi-Fi deployment is disclosed. A key feature is that no MAC protocol changes, nor client side modifications are needed to deploy the solution. Setting an optimal contention window can lead to throughput and latency improvements up to 155%, and 50%, respectively. Furthermore, an online learning method that efficiently finds the optimal contention window with minimal training data, and yields an average improvement in throughput of 53-55% during congested periods for a real traffic-volume workload replay in a Wi-Fi test-bed is demonstrated.

Algorithm to predict optimal Wi-Fi contention window based on load

Systems and methods for managing multi-channel network traffic

A method for dynamic allocation of communication resources includes (1) determining a risk-return characterization of a plurality of communication resource allocations across a plurality of communication channels in a communication system, (2) selecting a first allocation of the plurality of communication resource allocations from the risk-return characterization according to at least one predetermined criterium, and (3) automatically allocating communication resources among the plurality of communication channels according to the first allocation.

A content sharing platform for sharing content between collocated mobile devices in an ad-hoc private social group is disclosed. The content sharing platform enables users of collocated mobile devices to discover an ad-hoc private social group. A content group identifier identifying a content group is shared with users in the ad-hoc private social group. The content group identifier enables users in the content group to access a web user interface to share content with the content group. The users' interactions with the content are processed in real-time for all the collocated mobile devices in the content group. The content sharing platform displays context-aware and history-aware features of the content through the web user interface. Users of the content sharing platform may share, interact and collaborate with content in real-time in their collocated mobile devices.

Sharing content between collocated mobile devices in an ad-hoc private social group

Systems and methods for protecting and deduplicating streams of data in a cloud based platform. A platform is configured with multiple services and can communicate with multiple clients. The platform receives all requests at an endpoint and distributes the requests to workers using multiple queues. The platform may be stateless and is scalable. The meta-data is handled separately from the data in one example.

Scalable cloud hosted metadata service

A computer-implemented method, system, and non-transitory computer readable medium for device pairing for content sharing are disclosed. An encoded URL is accessed in a first device, the encoded URL associated with a second device. A content group identifier is provided to the second device. The second device is notified that content is ready to be pushed to the second device from the first device through the content group. Content is pushed from the first device to the second device through the content group.

Device pairing for content sharing

According to an example, a series of video frames may be accessed, in which a first set of the video frames depicts segments of an entity moving relative to other entities in the video frames and wherein a second set of the video frames depicts static content. In addition, the video frames in the first set of video frames may be generated into animated image files and the video frames in the second set of video frames into single image files. Furthermore, the animated image files and the single image files may be arranged into an interactive slide deck.

Interactive slide deck

In one example, a memory includes a data structure organized to include information resident in a number of databases geographically-partitioned according to a number of shards. The data structure includes a geographically-hashed look up table containing a number of geo-hash ranges associated with the shards and is organized to enable instructions to execute and access the ranges according to a number of characters in a generated geo-hash value. The data structure also includes a plurality of user data object tables that contain respective user data attributes and link to a particular server node and an associated geo-partitioned database.

Growing community of inventors

Sunnyvale, CA, United States of America

Thomas E Sandholm