Abstract: In one embodiment, an apparatus of an access point (AP) node of a network includes an interconnect interface to connect the apparatus to one or more components of the AP node and a processor to: access scheduling requests from a plurality of devices, select a subset of the devices for scheduling of resource blocks in a time slot, and schedule wireless resource blocks in the time slot for the subset of devices using a neural network (NN) trained via deep reinforcement learning (DRL).

Abstract: In one example, a head mounted display system includes at least one memory; and at least one processor to execute instructions to: detect a first position and a first view direction of a head of a user based on sensor data generated by at least one of an accelerometer, at least one camera, or a gyroscope at a first point in time; determine a latency associated with a time to cause an image to be presented on the display; determine a predicted position and a predicted view direction of the head of the user at a second point in time based on the latency; render, prior to the second point in time, the image for presentation on the display based on the predicted position and the predicted view direction of the head of the user; and cause the display to present the rendered image.

Abstract: In one embodiment, an apparatus comprises processing circuitry to: receive, via a communication interface, a compressed video stream captured by a camera, wherein the compressed video stream comprises: a first compressed frame; and a second compressed frame, wherein the second compressed frame is compressed based at least in part on the first compressed frame, and wherein the second compressed frame comprises a plurality of motion vectors; decompress the first compressed frame into a first decompressed frame; perform pixel-domain object detection to detect an object at a first position in the first decompressed frame; and perform compressed-domain object detection to detect the object at a second position in the second compressed frame, wherein the object is detected at the second position in the second compressed frame based on: the first position of the object in the first decompressed frame; and the plurality of motion vectors from the second compressed frame.

Abstract: A method can be performed by a first node for determining a parameter of physical (PHY) layer circuitry of a second node. The method can include implementing a cascaded hierarchy of techniques to determine, based on an electrical signal from a second node, a parameter of the PHY layer circuitry of the second node, and causing an antenna of the first node to transmit an electromagnetic wave consistent with the determined parameter.

Abstract: In one embodiment, an apparatus comprises a communication interface and a processor. The communication interface is to communicate with a plurality of devices. The processor is to: receive compressed data from a first device, wherein the compressed data is associated with visual data captured by sensor(s); perform a current stage of processing on the compressed data using a current CNN, wherein the current stage of processing corresponds to one of a plurality of processing stages associated with the visual data, and wherein the current CNN corresponds to one of a plurality of CNNs associated with the plurality of processing stages; obtain an output associated with the current stage of processing; determine, based on the output, whether processing associated with the visual data is complete; if the processing is complete, output a result associated with the visual data; if the processing is incomplete, transmit the compressed data to a second device.

Abstract: A method for coordinating communication amongst a plurality of mobile devices, includes generating joint transmission information describing transmission information for use by the plurality of mobile devices in transmitting data related to a cooperative communication message to a destination node and instructing a mobile device to transmit a coordination message to the plurality of mobile devices, wherein the coordination message includes the joint transmission information.

Abstract: In one embodiment, an apparatus comprises a memory and a processor. The memory is to store visual data associated with a visual representation captured by one or more sensors. The processor is to: obtain the visual data associated with the visual representation captured by the one or more sensors, wherein the visual data comprises uncompressed visual data or compressed visual data; process the visual data using a convolutional neural network (CNN), wherein the CNN comprises a plurality of layers, wherein the plurality of layers comprises a plurality of filters, and wherein the plurality of filters comprises one or more pixel-domain filters to perform processing associated with uncompressed data and one or more compressed-domain filters to perform processing associated with compressed data; and classify the visual data based on an output of the CNN.

Abstract: In one embodiment, an apparatus comprises a storage device and a processor. The storage device may store a plurality of compressed images comprising one or more compressed master images and one or more compressed slave images.

Abstract: In one example, a head mounted display system includes detecting a position of a head of a user of the head mounted display, predicting a position of the head of the user of the head mounted display at a time after a time that the position of the head of the user was detected, and rendering image data based on the predicted head position.

Abstract: In one example, a head mounted display system includes at least one memory; and at least one processor to execute instructions to: detect a first position and a first view direction of a head of a user based on sensor data generated by at least one of an accelerometer, at least one camera, or a gyroscope at a first point in time; determine a latency associated with a time to cause an image to be presented on the display; determine a predicted position and a predicted view direction of the head of the user at a second point in time based on the latency; render, prior to the second point in time, the image for presentation on the display based on the predicted position and the predicted view direction of the head of the user; and cause the display to present the rendered image.

Abstract: Generally discussed herein are systems, devices, and methods for routing interests and/or content in an information centric network. A router can include a memory and routing circuitry coupled to the memory, the routing circuitry configured to receive a packet, receive one or more attributes including at least one of (1) a network attribute, (2) a platform attribute, and (3) a content attribute, determine which neighbor node is to receive the packet next based on the received one or more attributes, and forward the packet to the determined neighbor node.

Abstract: System and techniques for information centric network (ICN) implemented content data networks (CDNs) are described herein. A directive to initiate a cache operation for content may be received at a gateway of an ICN. An interest packet may be constructed based on the directive. The interest packet may be transmitted on the ICN and a response to the interest packet received. Here, the response has a payload that corresponds to the content. The payload then may be cached at a local repository of the gateway.

Abstract: Generally discussed herein are systems, devices, and methods for managing content of an information centric network (ICN). A component of an ICN can include a memory including an extended content store that includes content from at least one other component of the ICN, and first attributes of the content, the first attributes including a content popularity value that indicates a number of requests for the content, and processing circuitry to increment the content popularity value in response to a transmission of a first content packet that includes the content, the first content packet transmitted in response to receiving an interest packet.

Abstract: In one embodiment, an apparatus comprises a communication interface and a processor. The communication interface is to communicate with a plurality of devices. The processor is to: receive compressed data from a first device, wherein the compressed data is associated with visual data captured by sensor(s); perform a current stage of processing on the compressed data using a current CNN, wherein the current stage of processing corresponds to one of a plurality of processing stages associated with the visual data, and wherein the current CNN corresponds to one of a plurality of CNNs associated with the plurality of processing stages; obtain an output associated with the current stage of processing; determine, based on the output, whether processing associated with the visual data is complete; if the processing is complete, output a result associated with the visual data; if the processing is incomplete, transmit the compressed data to a second device.

Abstract: In one embodiment, an apparatus comprises a memory and a processor. The memory is to store visual data associated with a visual representation captured by one or more sensors. The processor is to: obtain the visual data associated with the visual representation captured by the one or more sensors, wherein the visual data comprises uncompressed visual data or compressed visual data; process the visual data using a convolutional neural network (CNN), wherein the CNN comprises a plurality of layers, wherein the plurality of layers comprises a plurality of filters, and wherein the plurality of filters comprises one or more pixel-domain filters to perform processing associated with uncompressed data and one or more compressed-domain filters to perform processing associated with compressed data; and classify the visual data based on an output of the CNN.

Abstract: In one embodiment, an apparatus comprises a storage device and a processor. The storage device may store a plurality of compressed images comprising one or more compressed master images and one or more compressed slave images.

Abstract: In one embodiment, an apparatus comprises a processor to: identify a workload comprising a plurality of tasks; generate a workload graph based on the workload, wherein the workload graph comprises information associated with the plurality of tasks; identify a device connectivity graph, wherein the device connectivity graph comprises device connectivity information associated with a plurality of processing devices; identify a privacy policy associated with the workload; identify privacy level information associated with the plurality of processing devices; identify a privacy constraint based on the privacy policy and the privacy level information; and determine a workload schedule, wherein the workload schedule comprises a mapping of the workload onto the plurality of processing devices, and wherein the workload schedule is determined based on the privacy constraint, the workload graph, and the device connectivity graph.

Abstract: System and techniques for network coding in an information centric network (ICN) are described herein. A request for a first portion of first named data may be received. A response to the request for the first portion of the first named data may be obtained. The first portion may be combined with a second portion for second named data to create a set of network coded responses. Names for members of the set of network coded responses may be created based on a first name for the first portion and a second name for the second portion. A response to the request may be made with the set of network coded responses using the names for members of the set of network coded responses.

Abstract: A method for coordinating communication amongst a plurality of mobile devices, includes generating joint transmission information describing transmission information for use by the plurality of mobile devices in transmitting data related to a cooperative communication message to a destination node and instructing a mobile device to transmit a coordination message to the plurality of mobile devices, wherein the coordination message includes the joint transmission information.

Abstract: Hybrid rendering is described for a wearable display that is attached to a tethered computer. In one example a process include determining a position and orientation of a wearable computing device, determining a rate of motion of the wearable computing device, comparing the rate of motion to a threshold, if the rate of motion is above the threshold, then rendering a view of a scene at the wearable computing device using the position and orientation information, and displaying the rendered view of the scene.