Abstract: System and techniques for capability discovery in an information centric network (ICN) are described herein. An ICN node receives a discovery packet that includes a discovery type corresponding to an indication of a node capability requested by a source node of the discovery packet. First capability data, from an intermediate node, is extracted from the discovery packet. The first capability data is stored locally by ICN node. Second capability data from the ICN node is added to the discovery packet to create an expanded discovery packet. The expanded discovery packet is then communicated by the ICN node.

Abstract: Methods, systems, and computer programs are presented for implementing Personalized Mobility as a Service (PMaaS) to improve transportation services delivery. One storage medium includes instructions for detecting, by a mobility as a service (MaaS) system, a request for a trip from a user device of a user. The storage medium further includes instructions for mapping, using a model executing on the machine, the user to a persona from a plurality of persona models. Each persona model has one or more characteristics associated with users of the MaaS system. Further yet, the storage medium includes instructions for determining trip parameters for the trip based on the persona mapped to the user, the trip parameters defining one or more trip segments for the trip, and instructions for providing trip parameters to the user device.

Abstract: Systems, apparatuses, methods, and computer-readable media, are provided for distributed machine learning (ML) training using heterogeneous compute nodes in a heterogeneous computing environment, where the heterogeneous compute nodes are connected to a master node via respective wireless links. ML computations are performed by individual heterogeneous compute nodes on respective training datasets, and a master combines the outputs of the ML computations obtained from individual heterogeneous compute nodes. The ML computations are balanced across the heterogeneous compute nodes based on knowledge of network conditions and operational constraints experienced by the heterogeneous compute nodes. Other embodiments may be described and/or claimed.

Abstract: An example apparatus includes interface circuitry, machine-readable instructions, and at least one processor circuit to be programmed by the machine-readable instructions to access a first set of samples associated with a diffusion model, the first set of samples including a plurality of input data samples, generate a representation of the first set of samples, sample the representation of the first set of samples to generate a representation of a second set of samples, and generate the second set of samples from the representation of the second set of samples, the second set of samples including a plurality of output data samples, an output data sample corresponding to an input data sample and being different from the corresponding input data sample.

Abstract: System and techniques for information centric network (ICN) protocol for federated learning are described herein. An interest packet may be received on a first interface to start a federated learning round. Here, the interest packet includes a participant criterion and a federated learning round expiration. An entry, that includes the federated learning round expiration, is created in a pending interest table (PIT) for the interest packet. The interest packet is forwarded, in accordance with a forwarding information base (FIB), to a set of interfaces before the federated learning round expiration. When a data packet from a node, that meeting the participant criterion, is received in response to the interest packet, the data packet is forwarded on the first interface in accordance with the PIT entry.

Abstract: Various systems and methods for providing opportunistic placement of compute in an edge network are described herein. A node in an edge network may be configured to access a service level agreement related to a workload, the workload to be orchestrated for a user equipment by the node; modify a machine learning model based on the service level agreement; implement the machine learning model to identify resource requirements to execute the workload in a manner to satisfy the service level agreement; initiate resource assignments from a resource provider, the resource assignments to satisfy the resource requirements; construct a resource hierarchy from the resource assignments; initiate execution of the workload using resources from the resource hierarchy; and monitor and adapt execution of the workload based on the resource hierarchy in response to the execution of the workload.

Abstract: Packet recovery mechanisms for wireless networks, which improve end-to-end (e2e) reliability, are provided. First embodiments include packet retransmission between a receiver and a transmitter, wherein, if the transmitter cannot find a lost packet in its transmission buffer, the transmitter sends a First Sequence Number (FSN) report to the receiver to notify the receiver of a sequence number (SN) of an oldest (acknowledged) packet in the buffer. In response, the receiver does not report lost packets whose SN is older than the FSN. Second embodiments involve using a network coding algorithm to recover lost packets, wherein the transmitter sends a control message to the receiver that includes a coded packet to be recovered and information for decoding the coded packet. Other embodiments may be described and/or claimed.

Abstract: An apparatus of an edge computing node, a method, and a machine-readable storage medium. The apparatus is to decode messages from a plurality of clients within the edge computing network, the messages including respective coded data for respective ones of the plurality of clients; computing estimates of metrics related to a global model for federated learning using the coded data, the metrics including a gradient on the coded data; use the metrics to update the global model to generate an updated global model, wherein the edge computing node is to update the global model by calculating the gradient on the coded data based on a linear fit of the global model to estimated labels from the federated learning; and send a message including the updated global model for transmission to at least some of the clients.

Abstract: System and techniques for capability discovery in an information centric network (ICN) are described herein. An ICN node receives a discovery packet that includes a discovery type corresponding to an indication of a node capability requested by a source node of the discovery packet. First capability data, from an intermediate node, is extracted from the discovery packet. The first capability data is stored locally by ICN node. Second capability data from the ICN node is added to the discovery packet to create an expanded discovery packet. The expanded discovery packet is then communicated by the ICN node.

Abstract: Apparatuses of a user equipment (UE), a cellular base station, and radio access network (RAN) nodes are disclosed. An apparatus of a wireless communication device includes circuitry configured to measure reference signals received from a plurality of antennas of an other wireless communication device, and circuitry configured to cause one or more antennas of the wireless communication device to transmit information regarding the received reference signals back to the other wireless communication device to enable the other wireless communication device to estimate a utility function for different transmit parameter sets.

Abstract: Systems and methods of beamforming and improving mmWave communications for drones are described. Multiple RF chains are used to adapt the main beam to track changes without the use of pilot signals. To reduce interference, interfering signal power is eliminated by optimizing a non-Gaussian measure to extract the interferers. The AoA of signals from a target drone on neighbouring drones and location of the neighbouring drones and base stations are used to independently corroborate the location reported by the target drone. The base station provides additional synchronization signals below 6 GHz and restricts the search/measurement space in the vertical direction. The inherent sparse structure above 6 GHz is exploited by applying different beamformers on a sounding signal and estimating the AoA and impulse response. Variations of fully digital and hybrid beamforming architectures for multi-cell DL sync and CRS measurement are described.

Abstract: Embodiments of the present disclosure are directed towards devices and methods for identifying preferred access networks based at least in part on access network information including access network assistance information, steering policies, or access commands. In some embodiments, conflicts between access network information and access network discovery and selection function (ANDSF) policies may be rectified in identifying a preferred access network.

Abstract: A circuit arrangement includes a preprocessing circuit configured to obtain context information related to a user location, a learning circuit configured to determine a predicted user movement based on context information related to a user location to obtain a predicted route and to determine predicted radio conditions along the predicted route, and a decision circuit configured to, based on the predicted radio conditions, identify one or more first areas expected to have a first type of radio conditions and one or more second areas expected to have a second type of radio conditions different from the first type of radio conditions and to control radio activity while traveling on the predicted route according to the one or more first areas and the one or more second areas.

Abstract: A device to train a hyperdimensional computing (HDC) model may include memory and processing circuitry to train one or more independent sub models of the HDC model and transmit the one or more independent sub models to another computing device, such as a server. The device may be one of a plurality of devices, such as edge computing devices, edge or Internet of Things (IoT) nodes, or the like. Training of the one or more independent sub models of the HDC model may include transforming one or more training data points to one or more hyperdimensional representations, initializing a prototype using the hyperdimensional representations of the one or more training data points, and iteratively training the initialized prototype.

Abstract: System and techniques for device-specific connections in an information centric network (ICN) are described herein. A device is detected on a physical interface at an ICN node. A virtual interface is created for the device on the physical interface and the virtual device is added to a forward information base (FIB) entry. Then, when an interest packet with a name that corresponds to the device is received, the interest packet is forwarded to the device through the physical interface using the virtual interface based on the FIB entry.

Abstract: Packet recovery mechanisms for wireless networks, which improve end-to-end (e2e) reliability, are provided. First embodiments include packet retransmission between a receiver and a transmitter, wherein, if the transmitter cannot find a lost packet in its transmission buffer, the transmitter sends a First Sequence Number (FSN) report to the receiver to notify the receiver of a sequence number (SN) of an oldest (acknowledged) packet in the buffer. In response, the receiver does not report lost packets whose SN is older than the FSN. Second embodiments involve using a network coding algorithm to recover lost packets, wherein the transmitter sends a control message to the receiver that includes a coded packet to be recovered and information for decoding the coded packet. Other embodiments may be described and/or claimed.

Abstract: Apparatuses, methods and storage medium associated with computer-assisted or autonomous driving (CA/AD) vehicles are disclosed herein. In embodiments, CA/AD vehicles are members of a CA/AD vehicle social network (CASN) in which various CA/AD vehicles may form connections or relationships with one another. CA/AD vehicles that have an existing relationship or connection may share CASN information with one another. The CASN information may include authenticated and/or proprietary information. Other embodiments are also described and claimed.

Abstract: System and techniques for orchestrating a service with an interest packet in information centric networking are described herein. The interest packet includes a compound name that includes multiple ICN name components, and the interest packet includes a field with a list of ICN components. A device, after receiving the interest packet, locates an ICN name component from the multiple ICN name components that is represented in the list of ICN components. The device may then select an interface from multiple interfaces available to the device, the selection based on the ICN name component. The device may then transmit the interest packet via the interface.

Abstract: A wireless communication device includes a processor configured to select an offload processing task for performance by an edge computing device; cause a baseband modem to establish a direct wireless connection between the wireless communication device and the edge computing device; cause the baseband modem to send first data to the edge computing device via the direct wireless connection; and receive second data from the edge computing device, wherein the second data comprise a result of the offload processing task performed on the first data. The edge computing device includes a processor configured to receive, from a user device, offloaded data to be processed according to an offload processing task; execute the offload processing task on the offloaded data; and cause the radio via the interface to wirelessly send a result of the executed offload processing task via a direct wireless connection with the user device.

Abstract: A central trajectory controller including a cell interface configured to establish signaling connections with one or more backhaul moving cells and to establish signaling connections with one or more outer moving cells, an input data repository configured to obtain input data related to a radio environment of the one or more outer moving cells and the one or more backhaul moving cells, and a trajectory processor configured to determine, based on the input data, first coarse trajectories for the one or more backhaul moving cells and second coarse trajectories for the one or more outer moving cells, the cell interface further configured to send the first coarse trajectories to the one or more backhaul moving cells and to send the second coarse trajectories to the one or more outer moving cells.