AT&T Intellectual Property I, LP

Emory University

Harvard College

University of Southern California

Yaron Kanza

Arun Jotshi

Velin Kounev

Divesh Srivastava

Tamraparni Dasu

Krystian Czapiga

Raghvendra Savoor

Theodore Donald Johnson

Vladislav Shkapenyuk

Eleftherios Koutsofios

Balachander Krishnamurthy

Philip E Brown

Rajat Malik

Li Xiong

Shuaicheng Ma

Teddy Chu

Gordon Woodhull

Sivaramakrishnan Ramanathan

Weiwei Duan

Poornima Suresh

Gopalakrishnan Meempat

Danielle Liu

Gaurav Thakur

Joshua Whitney

James Klosowski

Philip M Brown

Pramod Jamkhedkar

Chih Chien Huang

Fei Wu

Aarthi Reddy

Johan Muedsam

Jean Luo

Matt Dugan

Minian Yu

Caroline Stone

David Wood

Serkan Isci

Divith Aruni Babu

Laks V S Lakshmanan

Jelena Mirkovic

Aspects of the subject disclosure may include, for example, detecting data streams by a processing system including a processor, wherein the processing system is associated with an anomaly detection and alerting system in which stream processing and model maintenance is decoupled from one another, and wherein one or more dedicated virtual machines (VMs) store and maintain anomaly detection and alerting models, based on the detecting, causing, by the processing system, a plurality of stream-processing VMs to be instantiated for processing the data streams, and managing, by the processing system, data stream assignments for the plurality of stream-processing VMs based on monitoring of one or more conditions, wherein the plurality of stream-processing VMs process assigned data streams by executing instances of the anomaly detection and alerting models, and provide model outputs to the one or more dedicated VMs for updating of the anomaly detection and alerting models. Other embodiments are disclosed.

System and method for cloud-based anomaly detection and alerting for streaming data

In one example, a method performed by a processing system including at least one processor includes creating a geospatial model of an environment in which a cellular network is to be deployed, transforming, for each cellular antenna of a proposed antenna layout of the cellular network, a radiation pattern of the each cellular antenna into a signal strength array, to create a plurality of signal strength arrays, augmenting, for each signal strength array of the plurality of signal strength arrays, the each signal strength array with at least one parameter of a corresponding cellular antenna of the proposed antenna layout and at least one value describing the environment in which the cellular network is to be deployed, and estimating a coverage of the proposed antenna layout based on the signal strength array, as augmented, using a machine learning model.

Machine-learning-based wireless planning using antenna radiation patterns

Aspects of the subject disclosure may include, for example, instantiating a virtual smartphone in a cloud infrastructure, installing a smartphone application on the virtual smartphone, receiving input sensor data from a physical user device, providing the input sensor data to the smartphone application on the virtual smartphone, receiving output data from the smartphone application on the virtual smartphone, and providing the output data to the physical user device. Other embodiments are disclosed.

Cloud resources for smartphone applications

Aspects of the subject disclosure may include, for example, a device including a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, define operations of modules that monitor a computational hierarchy, the modules include a first module for generating base alerts with a hierarchical key associated with an operation of the computational hierarchy and for rolling up the base alerts based on the computational hierarchy, resulting in rolled-up base alerts; a second module for generating super alerts from a concentration of the rolled up base alerts; and a third module comprising a first plurality of models that selects the super alerts based on priority, persistence of anomalies, pervasiveness of the super alerts generated, recency, or a combination thereof, generates a smart alert based on voting on the super alerts selected by the first plurality of models, and presents the smart alert on a user interface. Other embodiments are disclosed.

Architecture for scalable smart alerting across a multitude of data streams

Aspects of the subject disclosure may include, for example, a device having a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations of: receiving a series of values from a data stream generated by one or more equipment in a communications network; creating a first window of values received before a first point in time and a second window of values received on or after the first point in time; comparing a distribution of values in the first window and values in the second window to compute a distance at the first point in time; repeating the creating and comparing at subsequent points in time after the first point in time, thereby generating a series of distances; computing a z-score for a first distance in the series of distances; generating an alert responsive to the z-score exceeding a threshold; and storing the alert in a log of alerts. Other embodiments are disclosed.

System and method for detecting anomalous changes in data streams and generating textual explanations

A method performed by a processing system including at least one processor includes applying a contextual filter to mask a portion of at least one of: an input of a software application, an output of the software application, or an underlying dataset of the software application, where the contextual filter simulates a limitation of a user of the software application, executing the software application with the contextual filter applied to the at least one of: the input of the software application, the output of the software application, or the underlying dataset of the software application, collecting ambient data during the executing, and recommending, based on a result of the executing, a modification to the software application to improve at least one of: an accessibility of the software application or an inclusion of the software application.

Testing accessibility of geospatial applications using contextual filters

An example method performed by a processing system includes obtaining a light detecting and ranging point cloud of a building, where the point cloud includes a plurality of points, and where each point is associated with a set of (x,y,z) coordinates. A first point of the plurality of points is assigned to a subset of the plurality of points that is associated with the building, where the subset includes points whose (x,y) coordinates fall within a footprint of the building. The first point is grouped into a first cluster according to at least one of: a (z) coordinate of the first point and a gradient to which the first point belongs. A first prism formed by the first cluster is constructed. A model of the building is stored as a plurality of connected prisms, where the plurality of connected prisms includes the first prism.

Constructing compact three-dimensional building models

In one example, the present disclosure describes a device, computer-readable medium, and method for implementing programmable security specifications in home routers. For instance, in one example, a method performed by a processing system including at least one processor includes monitoring network traffic flowing into and out of a home network that is connected to a core network via a gateway device, constructing a model of network traffic flowing into and out of the home network, based on the monitoring, detecting an anomaly in the model of the network traffic, generating a rule based on the anomaly, where the rule specifies an action to be taken when a match condition related to the anomaly is detected, and deploying the rule on the gateway device.

Implementing network security rules in home routers

Aspects of the subject disclosure may include, for example, a non-transitory, machine-readable medium, comprising executable instructions that, when executed by a processing system including a processor, facilitate performance of operations including receiving a call; selecting a next carrier to handoff the call; generating a call data record (CDR) for the handoff to the next carrier; encrypting the CDR using a call encryption key, thereby creating an encrypted CDR; encrypting the encrypted CDR using a committee encryption key, thereby creating a double encrypted CDR; recording the double encrypted CDR to a blockchain; and sending the call encryption key to the next carrier. Other embodiments are disclosed.

System and method for mitigating international revenue share fraud

A processing system including at least one processor may obtain at least one search term and an identity of a searcher, identify individuals who are each either a one-step or two-step association of the searcher, identify first documents associated with the individuals and associated with the search term(s), calculate, for each individual, a score based upon citations of second documents to documents associated with the individual from among the first documents, generate an invitation to at least one individual to appear in a search result, and obtain a consent from the at least one individual. The processing system may then present the search result as an ordered list of at least a portion of the individuals, where the ordered list is ordered by the score for each individual, and where the at least the portion of the plurality of individuals includes the at least one individual.

Confidentiality preserving intraorganizational expert search

Aspects of the subject disclosure may include, for example, a process for selecting equipment locations such as of cellular antennas, based on a combination of a geospatial grid representation of a planning area and optimization algorithms (which can be combined with propagation models and a 3D model of the world) where the optimization algorithm can select a deployment from a large space of options and would make RAN planning much more efficient. Other embodiments are disclosed.

RAN planning using grid-based optimization

Aspects of the subject disclosure may include, for example, a device with a processing system including a processor; and a memory that stores executable instructions that, when executed by the processing system, facilitate performance of operations including receiving a first record of sending a file and a hash for the file from a sender of the file; recording the first record on a blockchain; providing the first record to a receiver of the file; and monitoring a predetermined time period in which to receive a second record of receiving the file and the hash for the file. Other embodiments are disclosed.

Blockchain-powered ledger for a data supply chain

A processing system may obtain usage volume information for endpoint devices for at least one cell site of a cellular network, determine at least one earning value of the at least one cell site based upon a summation of an earning metric of each of the endpoint devices for the at least one cell site, the earning metric comprising for each of the endpoint devices in a given time period: a total earning for the cellular network from the endpoint device times a ratio of the usage volume via the at least one cell site divided by the total usage volume via the cellular network, train a prediction model to predict an earning value of a new cell site, based upon geospatial features of the at least one cell site as predictor factors, and determine a predicted earning value of the new cell site via the prediction model.

Geospatial-based forecasting for access point deployments

Aspects of the subject disclosure may include, for example, network deployment or radio-propagation computation based on a combination of photon mapping and machine learning including supporting near-real-time computation of the radio transmissions for different layouts of antennas and allowing examination of a large variety of antenna locations and layouts, changing configuration details, e.g., tilting antennas or optimally selecting the sector that each antenna covers, and so on. Other embodiments are disclosed.

Real-time ML-supported radio propagation computation for RAN planning

Growing community of inventors

Fair Lawn, NJ, United States of America

Yaron Kanza