San Diego State University Research Foundation

The University of Alabama

Servicenow, Inc.

Qualcomm Incorporated

V-enablo, Inc.

Sunil Kumar

Fei Hu

Harry Thomas Nelson

Nikhil Prashant Bendre

Khosrow Jian Motamedi

Barbara J Bailey

Yeqing Wu

Ke Bao

Chandra Kholia

Sreedhar Gudala

Qian Mao

Kumar Gopal Rao

Francis Page

Lei Hu

Pak Kin Wong

Seethal Paluri

Xin Li

Dipanshu Sharma

Non-volatile memory may contain definitions of: (i) a plurality of message queue implementations respectively associated with different queue behaviors, the different queue behaviors specified by corresponding sets of modes, and (ii) an application programming interface (API) through which applications can access one or more message queues. One or more processors may be configured to: create a message queue of a particular message queue type, supported by a corresponding message queue implementation, by specifying a set of modes corresponding to a queue behavior; receive, from a producing application and by way of the API, one or more messages for the message queue; store the one or more messages in a data structure associated with the message queue; receive, from a consuming application and by way of the API, a request to read from the message queue; and provide a message from the message queue to the consuming application.

Message queue architecture and interface for a multi-application platform

Disclosed and described herein are smart, high-speed UV communication protocols, inspired by the biological principles. The disclosed and described protocols use a 'pipe' routing topology to deliver large amount of data among the UVs equipped with multi-beam antennas. The disclosed and described embodiments include bio-inspired pipe routing and adaptive batch coding (ABC) based congestion control. In regard to bio-inspired pipe routing, a human's brain uses highly cooperative neuro cells to memorize everything. Inspired by neuro networks, a pipe architecture with high-throughput node-to-node data delivery is disclosed and described herein. The pipe routing uses multi-beam antennas to achieve parallel data transmission. In regard to ABC based congestion control, a new network coding called ABC is disclosed, which can minimize traffic congestion occurrences in the above pipe routing. The disclosed and described transport layer protocol includes both end-to-end reliability and congestion control.

Intelligent high-speed unmanned vehicle communications via bio-inspired multi-beam pipe transmission

A MAC design for Ku-band mobile wireless mesh network with multi-beam smart antennas is disclosed. This MAC includes an overlay control that separates the collision domain. It also has lower layer CSMA-like scheme. The disclosed design includes an enhanced PCF and an enhanced DCF for two purposes: (1) exploiting multi-beam concurrent communication capability (2) supporting QoS and mission-based communications. An efficient time synchronization scheme is also disclosed to ensure all beams can concurrently send data to the star node. Finally, ARMA or HMM based prediction schemes are disclosed to predict future traffic profile in each beam. This helps the star node to better prepare the queue content and schedule information.

Intelligent multi-bean medium access control in ku-band for mission-oriented mobile mesh networks

Disclosed herein are systems and methods directed to routing in the wireless mesh network (WMN) with multi-beam directional antennas (MBDAs). The disclosed systems and methods describe Ripple-Diamond-Chain (RDC) shaped routing, systematic link quality modeling and artificial intelligence (AI) augmented path link selection. In simulations, real-time video as well as other types of traffic types are used to validate the high-throughput, quality of service (QoS)-differentiated, multi-beam routing efficiency of the disclosed systems and methods, as well as the intelligent path determination in dynamic WMN environments.

Artificial intelligence-augmented, ripple-diamond-chain shaped rateless routing in wireless mesh networks with multi-beam directional antennas

A cross-layer encoder for providing UEP encoding of video data configured to provide UEP encoding of video data at an application layer of a transmission channel by receiving video packets having first and second priority levels, applying first and second coding schemes to video packets having first and second priority levels, respectively, and transmitting video frames having first and second priority levels. The cross-layer encoder can be configured to provide UEP encoding of video data at a physical layer of the transmission channel by receiving encoded video frames having first and second priority levels, applying third and fourth coding schemes to video frames having first and second priority levels, respectively, and transmitting cross-layer encoded video frames having first and second priority levels. The first through fourth coding schemes can generate different percentages of the total coding overhead based on first and second priority levels, respectively.

Multi-layer integrated unequal error protection with optimal parameter determination for video quality granularity-oriented transmissions

Circuits and methods for a system on a chip having non-uniform channel spacings is provided. In an example, a chip is provided that includes a first functional block having a rectilinear shape, the first processing unit having on a side a plurality of channel spacings. A first channel spacing of the plurality of channel spacings is positioned in contact with the side and a second functional block. A second channel spacing of the plurality of channel spacings is positioned in contact with the side and the second functional block. The width of the second channel spacing is non-uniform with the width of the first channel spacing.

Rectilinear macros having non-uniform channel spacing

The invention relates to systems and methods for prioritizing video slices of H.264 video bitstream comprising: a memory storage and a processing unit coupled to the memory storage, wherein the processing unit operates to execute a low complexity scheme to predict the expected cumulative mean squared error (CMSE) contributed by the loss of a slice of H.264 video bitstream, wherein the processing unit operates to execute a series of actions comprising assigning each slice a predicted value according to the low complexity scheme; extracting video parameters during encoding process, said video parameters; and using a generalized linear model to model CMSE as a linear combination of the video parameters, wherein the video parameters are derived from analytical estimations by using a Generalized Linear Model (GLM) over a video database, encompassing videos of different characteristics such as high and low motion, camera panning, zooming and still videos, further comprising wherein the GLM is constructed in a training phase as follows: determining the distribution of the computed CMSE to be a Normal distribution with the Identity link function; sequentially adding covariates using the forward selection technique where by the best model is evaluated at each stage using the Akaike's Information Criterion (AIC); the training phase of the model generates regression coefficients; the final model is validated through the testing phase by predicting the CMSE for different video sequences, not in the training database; and by using the regression coefficients, the expected CMSE values are predicted for each slice.

Slice priority prediction system for H.264 video

Multi-modal system which enables documents to be interpreted as either or both of voice browser-based documents and/or visual browser-based documents for a thin client such as a portable telephone. Special techniques and additions are added into the document to enable the document to be converted between voice markup and visual markup languages. In addition, the document can be simultaneously viewed in both of the voice markup and the visual markup languages. Special techniques are used to allow keeping track of the browsing position within this document.

Growing community of inventors

San Diego, CA, United States of America

Sunil Kumar