Abstract: A method for selecting between a plurality of paths for sending an encrypted packet from a source endpoint to a destination endpoint is provided. The method selects a first path of the plurality of paths for sending the encrypted packet from the source endpoint to the destination endpoint, each of the plurality of paths associated with a different one of a plurality of source ports, the encrypted packet being encrypted based on a security association established between the source endpoint and the destination endpoint in accordance with an IPSec protocol. The method further encapsulates, based on the SA having NAT-T enabled, the encrypted packet with a UDP header having a first source port associated with the first path. The method then transmits the encapsulated encrypted packet from the source endpoint to the destination endpoint via the first path.

Abstract: An example method of propagating fault domain topology information in a distributed container orchestration system includes: receiving, at control plane software executing in a data center, the fault domain topology, which includes tags for a protection group and fault domains for remote sites in communication with the data center; deploying, by a master server of the distributed container orchestration system that executes in the data center, a node pool comprising virtual machines (VMs) executing in servers of the remote sites, the VMs being nodes of the distributed container orchestration system in which containers execute; determining, by a controller of the master server, relationships among the VMs, the servers, the protection group, and the fault domains based on state of resources maintained by the master server; and providing, by the controller, labels to the servers for associating the tags of the protection group and the fault domains to the VMs.

Abstract: An example method of diagnosing remote sites of a distributed container orchestration system includes: receiving, at a management cluster, definition of a test suite custom resource; deploying, in response to the test suite custom resource, a first pod in the management cluster; deploying, by the first pod, a second pod in a server of a first remote site of the remote sites; checking, by the second pod, configuration of the server that includes an additional pod executing alongside the second pod, at least one virtual machine (VM) in which the second pod and the additional pod execute, a hypervisor configured to support the at least one VM, and a hardware platform on which the hypervisor executes; and returning test data from the second pod to the first pod, the test data including results of the step of checking the configuration of the server.

Abstract: The disclosure provides an approach for simulating a virtual environment. A method includes simulating, using a virtualization simulator, a plurality of hosts; simulating, using the virtualization simulator, a plurality of virtual computing instances (VCIs) associated with the plurality of simulated hosts, based on information obtained from a cluster application programming interface (API) provider; creating, using a virtualization simulator operator, one or more node simulator schedulers; creating, using the one or more node schedulers, a node simulator; simulating, using the node simulator, a plurality of guest operating systems (OSs) associated with the plurality of simulated VCIs; and joining the plurality of simulated guest OSs to one or more node clusters in a data center via an API server.

Abstract: An example method of updating device firmware in a distributed container orchestration system includes: receiving, at a master server executing in a data center, a definition for a firmware custom resource; obtaining, by an operator of the master server in response to the firmware custom resource, a firmware file set; providing, from the operator to a plurality of remote sites in communication with the data center, the firmware file set; and executing, by servers at the plurality of remote sites, updates of firmware for devices of the servers.

Abstract: Various aspects include approaches for managing tinnitus in a user. In some particular aspects, a computer-implemented method of managing tinnitus of a user with at least one wearable device includes: actuating, according to a prescribed pattern and using the at least one wearable device: a) an electro-acoustic transducer to provide an audio output to the user, and b) a contact element to apply vibration to a body part of the user, where the prescribed pattern both stimulates the nervous system of the user and delivers a sound to the user, which together mitigate the tinnitus.

Abstract: Systems and techniques are described for monitoring network communications using a distributed firewall. One of the techniques includes receiving, at a driver executing in a guest operating system of a virtual machine, a request to open a network connection from a process associated with a user, wherein the driver performs operations comprising: obtaining identity information for the user; providing the identity information and data identifying the network connection to an identity module external to the driver; and receiving, by a distributed firewall, data associating the identity information with the data identifying the network connection from the identity module, wherein the distributed firewall performs operations comprising: receiving an outgoing packet from the virtual machine; determining that the identity information corresponds to the outgoing packet; and evaluating one or more routing rules based at least in part on the identity information.

Abstract: Various implementations include conversation assistance audio devices with settings that are adjustable based upon user feedback. In some cases, a computer-implemented method of personalizing a conversation assistance audio device includes: receiving a command from a user for assistance with audio settings in the conversation assistance audio device; applying a baseline set of audio settings to the conversation assistance audio device in response to receiving the user command for assistance; receiving a user command to change the baseline set of audio settings; and applying a modified set of audio settings to the conversation assistance audio device in response to receiving the user command to change the baseline set of audio settings, wherein the modified set of audio settings are applied based upon usage of the conversation assistance audio device and a population model of usage of similar conversation assistance audio devices.

Abstract: Various implementations include systems for processing audio signals. In particular implementations, a process includes receiving an audio signal, wherein the audio signal includes a speech component of the user and a noise component; filtering the audio signal with a self-speech filter that utilizes an intrinsic user vector to filter out the speech component, wherein the intrinsic user vector is determined based on a voice input of the user; and outputting a filtered audio signal in which the speech component of the user has been substantially removed from the audio signal.

Abstract: Systems and techniques are described for monitoring network communications using a distributed firewall. One of the techniques includes receiving, at a driver executing in a guest operating system of a virtual machine, a request to open a network connection from a process associated with a user, wherein the driver performs operations comprising: obtaining identity information for the user; providing the identity information and data identifying the network connection to an identity module external to the driver; and receiving, by a distributed firewall, data associating the identity information with the data identifying the network connection from the identity module, wherein the distributed firewall performs operations comprising: receiving an outgoing packet from the virtual machine; determining that the identity information corresponds to the outgoing packet; and evaluating one or more routing rules based at least in part on the identity information.

Abstract: A computer-implemented method, medium, and system for implementing a pluggable diagnostic tool for Telco radio access network (RAN) troubleshooting are disclosed. In one computer-implemented method, one or more containerized network function (CNF) instances are generated in a container orchestration platform by a test system and by using a telecommunication cloud automation (TCA) platform executed in the container orchestration platform, where the test system is onboarded to the TCA platform, and the one or more CNF instances are associated with 5G RAN. A customer resources (CR) file is received by the test system, where the CR file defines multiple test cases associated with validation of the TCA platform. The CR file is transmitted to a cluster of nodes in the container orchestration platform. The validation of the TCA platform is executed at the cluster of nodes based on the one or more CNF instances and the CR file.

Abstract: Various implementations include systems for processing audio signals to remove artifacts introduced by a machine learning system in challenging environments. In particular implementations, a method includes generating a processed audio signal for a hearing assistance device in which the processed audio signal is intended to perceptually dominate a user auditory experience, including: processing an unprocessed audio signal received by the hearing assistance device, wherein the processing includes utilizing a machine learning (ML) system to generate an ML enhanced audio signal; determining a mixing coefficient from an environmental noise assessment; mixing the ML enhanced audio signal with the unprocessed audio signal using the mixing coefficient to generate the processed audio signal; and outputting the processed audio signal.

Abstract: Various implementations include systems for processing audio signals to remove artifacts introduced by a machine learning system in challenging environments. In particular implementations, a method includes generating a processed audio signal for a hearing assistance device in which the processed audio signal is intended to perceptually dominate a user auditory experience, including: processing an unprocessed audio signal received by the hearing assistance device, wherein the processing includes utilizing a machine learning (ML) system to generate an ML enhanced audio signal; determining a mixing coefficient from an environmental noise assessment; mixing the ML enhanced audio signal with the unprocessed audio signal using the mixing coefficient to generate the processed audio signal; and outputting the processed audio signal.

Abstract: The technology described in this document can be embodied in a computer-implemented method that includes receiving identification information associated with a geographic location. The identification information includes one or more features that affect an acoustic environment of the geographic location at a particular time. The method also includes determining one or more parameters representing at least a subset of the one or more features, and estimating at least one acoustic parameter that represents the acoustic environment of the geographic location at the particular time. The at least one parameter can be estimated using a mapping function that generates the estimate of the at least one acoustic parameter as a weighted combination of the one or more parameters. The method further includes presenting, using a user-interface displayed on a computing device, information representing the at least one acoustic parameter estimated for the geographic location for the particular time.

Abstract: A system includes an in-ear acoustic device that is configured to sit at least partially within a user's ear canal and a head-worn electronic device that is supported on a user's body outside of the user's ear canal. The in-ear acoustic device includes a first receiver and a first coil. The head-worn electronic device includes a second coil that is configured to communicate with the first coil via near-field magnetic inductance (NFMI) communication. The head-worn electronic device is configured to transmit a first processed audio signal to the in-ear acoustic device via NFMI communication, and the first processed audio signal is used to drive the first receiver.

Abstract: Various implementations include systems for processing audio signals. In particular implementations, a system includes at least one microphone configured to capture acoustic signals; a wearable hearing assist device configured to amplify captured acoustic signals from the at least one microphone and output amplified audio signals to a transducer; a voice activity detector (VAD) configured to detect voice signals of a user from the captured acoustic signals; and a voice suppression system configured to suppress the voice signals of the user from the amplified audio signals being output to the transducer.

Abstract: Various implementations include control mechanisms for managing hearing aid usage. In some cases, an interface with a representation of the hearing aid in space is used to control audio functions in the device. In other cases, directionality of the device is controlled based upon the user's visual focus direction. In additional cases, the operating mode of the device is adjustable based upon the signature of a nearby acoustic signal.

Abstract: For a host that executes one or more guest virtual machines (GVMs), some embodiments provide a novel virtualization architecture for utilizing a firewall service virtual machine (SVM) on the host to check the packets sent by and/or received for the GVMs. In some embodiments, the GVMs connect to a software forwarding element (e.g., a software switch) that executes on the host to connect to each other and to other devices operating outside of the host. Instead of connecting the firewall SVM to the host's software forwarding element that connects its GVMs, the virtualization architecture of some embodiments provides an SVM interface (SVMI) through which the firewall SVM can be accessed to check the packets sent by and/or received for the GVMs.

Abstract: An audio enhancement method includes receiving a first plurality of input signals representative of audio captured using an array of two or more sensors, the first plurality of input signals characterized by a first signal-to-noise ratio (SNR), with the audio being the signal-of-interest. The method also includes receiving a second input signal representative of the audio, the second input signal characterized by a second SNR. The second SNR is higher than the first SNR. The method further includes combining the first plurality of input signals and the second input signal to generate one or more driver signals, and driving one or more acoustic transducers using the one or more driver signals to generate an acoustic signal representative of the audio. The driver signals include spatial information derived from the first plurality of input signals, and are characterized by a third SNR that is higher than the first SNR.

Abstract: Various implementations include systems for processing audio signals. In particular implementations, a process includes receiving an audio signal, wherein the audio signal includes a speech component of the user and a noise component; filtering the audio signal with a self-speech filter that utilizes an intrinsic user vector to filter out the speech component, wherein the intrinsic user vector is determined based on a voice input of the user; and outputting a filtered audio signal in which the speech component of the user has been substantially removed from the audio signal.