Abstract: Systems and techniques for mission critical (MC) push notification mechanism in a high-reliability (HR) information centric network (ICN) are described herein. For example, a node may test network links to other nodes to classify the other nodes into proximate nodes and non-proximate nodes based on a reception metric. The node may then elect a set of leader nodes from the proximate nodes. Here, the set of leader nodes are selected based on link quality between respective leader nodes and non-proximate nodes. The node may detect an MC event and create an ICN data packet that contains data from the MC event. The node may then transmit the ICN data packet to the set of leader nodes that then relay the ICN data packet to the non-proximate nodes.

Abstract: Systems, apparatuses and methods may provide for vehicle technology that detects one or more differences between a crowdsourced map of an ambient environment and a real-time volumetric map of the ambient environment and sends a first message via a vehicle-to-vehicle (V2V) link, wherein the difference(s) are represented in the first message at a first resolution. Additionally, the vehicle technology sends a second message via a vehicle-to-infrastructure (V2I) link, wherein the difference(s) are represented in the second message at a second resolution, and wherein the first resolution is less than the second resolution. Moreover, server technology may integrate a first octree representation and a second octree representation into a dynamic layer associated with the crowdsourced map.

Abstract: Systems and techniques for information centric network (ICN) emergency data collection are described herein. For example, an event coverage area may be measured. An interest packet may be transmitted to map nodes within the coverage area. In an example, the interest packet specifies a group prefix. A group of nodes that respond to the interest packet may be selected as event detecting nodes. Then, an event subscription interest packet may be transmitted to the event-detecting nodes.

Abstract: An embodiment of a semiconductor package apparatus may include technology to generate first name information corresponding to data and/or content for an autonomous vehicle to represent vehicular application information based on requirements of the vehicular application information, and generate second name information corresponding to a chain of functions for an autonomous vehicle based on the requirements of the vehicular application information. Another embodiment may include technology to identify a cluster head for a cluster of autonomous vehicles, utilize the cluster head to assist in-networking caching of data and/or functions, utilize the cluster head to coordinate discovery of availability of functions, data cache resources, and/or compute resources in a proximity of the cluster head, and utilize the cluster head to coordinate producer mobility and/or consumer mobility. Other embodiments are disclosed and claimed.

Abstract: Techniques are provided for optimizing the operations of an ICN, particularly for an ICN with clustered nodes. A cluster head node may function as an orchestrator and a coordinator for efficient caching, routing, and computing and for co-existence of ICN and IP nodes in the network. A content store of an ICN router may include an indication of the time after which data expires and the new data is to be swapped in place of the expired data after that point in time. Digital rights management (DRM) enforcement is provided by managing access to a DRM engine in at least one of the ICN nodes in a cluster. Congestion control is provided by minimizing the number of ICN scoped interest requests and thereby minimizing the potentially high volume of data responses. These techniques optimize interest packet forwarding and processing through collaboration with neighboring ICN nodes.

Abstract: Systems and techniques for quality-of-service (QoS) in cellular information centric network (ICN) are described herein. To this end, QoS characteristics may be obtained for an ICN packet. The QoS characteristics may then be applied to the ICN packet. The ICN packet may then be transmitted in accordance with the QoS characteristics.

Abstract: Systems, methods, and computer-readable media are provided for network access technology (NAT)-based packet network provenance. In disclosed embodiments, each node in a network encapsulates and/or encodes received packets with network interface information in addition to attestation information. The network interface information indicates a type of NAT used to forward the packet to a next node or hop in a network path. Each node in the network implements protocol stack that includes a multi-interface translation layer below a networking layer and above the layer 2 protocol stacks of various communication protocols. The multi-interface translation layer determines the type of NAT to be used to forward received packets to the next hop, and encapsulates the received packets with an indication of the determined NAT to be used to forward the packet. Other embodiments are disclosed and/or claimed.

Abstract: Systems and techniques for node-density aware interest packet forwarding in a dynamic ad hoc information centric network (ICN) are described herein. For example, a next interest packet to forward may be obtained at a network node. A time period to hold the next interest packet before forwarding may be calculated based on node density in the network. The node may then broadcast the next interest packet upon expiration of a timer set to the time period and started when the next interest packet was obtained.

Abstract: Methods, systems, and computer programs are presented for sharing information among Mobility as a Service (MaaS) providers to improve service delivery while protecting data privacy. A first MaaS system comprises means for receiving, from a second MaaS system, a request to predict demand generated by the first MaaS system for user trips that transfer from the first MaaS system to the second MaaS system. Further, the first MaaS system comprises means for predicting, in response to the request, the demand generated by the first MaaS system using a predictor model executing at the first MaaS system on a trusted execution environment (TEE) to access data of the first MaaS system. Further yet, the first MaaS system comprises means for sending the predicted demand to the second MaaS system.

Abstract: Disclosed herein are systems and methods for vehicle-occupancy-based and user-preference-based smart routing, and autonomous volumetric-occupancy measurement. In an embodiment, a system is configured to receive from a user device associated with a user, a routing-options request for routing options between two locations, and to responsively identify one or more routing options between the two locations based at least in part on occupancy data for a vehicle that would be utilized for at least a portion of at least one of the identified routing options. The occupancy data is based on an output of an automated occupancy-measurement system onboard the vehicle. The system is also configured to provide the one or more identified routing options to the user device. In some embodiments, the occupancy data is obtained using volumetric-occupancy measurement. Some embodiments relate to volumetric-occupancy measurement conducted by autonomous mesh nodes.

Abstract: Systems and techniques for mobility-as-a-service for user experience are described herein. An orchestration log may be maintained that includes current orchestration data. An orchestration backup record may be generated that includes alternate MaaS nodes on the MaaS network. It may be determined that connectivity is lost to a first orchestration container hosted by a first MaaS node. An orchestration container is generated using the orchestration log to maintain orchestration functionality. An available second MaaS node is identified from the alternate MaaS nodes. The orchestration container may be transferred to the second MaaS node.

Abstract: V2X trusted agents provide technical solutions for technical problems facing falsely reported locations of connected vehicles within V2X systems. These trusted agents (e.g., trusted members) may be used to detect an abrupt physical attenuation of a wireless signal and determine whether the attenuation was caused by signal occlusion caused by the presence of an untrusted vehicle or other untrusted object. When the untrusted vehicle is sending a message received by trusted agents, these temporary occlusions allow trusted members to collaboratively estimate the positions of untrusted vehicles in the shared network, and to detect misbehavior by associating the untrusted vehicle with reported positions. Trusted agents may also be used to pinpoint specific mobile targets. Information about one or more untrusted vehicles may be aggregated and distributed as a service.

Abstract: Systems and techniques for micro payments in a mobility-as-a-service (MaaS) network are described herein. A mobility task may be received for execution by a MaaS node of the MaaS network. An electronic contract may be established with a requestor of the task. A payment transaction may be initiated based on the mobility task and the electronic contract. The mobility task may be submitted for execution by the MaaS node using resources of the MaaS node. An amount of the payment may be transferred from an electronic account of the requestor to an electronic account of the MaaS node.

Abstract: Various systems and methods for improving connectivity of a Mobility-as-a-Service (MaaS) node are described herein, including categorizing MaaS communication traffic of a MaaS node into different levels of priority and controlling duplication or repetition of the MaaS communication traffic using the categorized level of priority of the MaaS communication traffic.

Abstract: A system for managing a fleet of vehicles in a MaaS network includes a scheduling subsystem configured to retrieve vehicle parameters associated with the fleet of vehicles, the vehicle parameters including a range of travel estimate for each of the vehicles in the fleet. The subsystem retrieves infrastructure resource availability information associated with at least one infrastructure resource used by the fleet of vehicles, and historical usage information associated with the at least one infrastructure resource. The subsystem applies a machine learning technique using the vehicle parameters, the infrastructure resource availability information, and the historical usage information to generate a scheduling instruction. The scheduling instruction is communicated to the fleet of vehicles, the scheduling instruction for scheduling usage of the at least one infrastructure resource by one or more of the vehicles in the fleet.

Abstract: Methods are described for providing routing updates in information-centric networks (ICNs) by using a centralized ICN routing coordination unit to exchange updated routing tables with certain popular nodes in popular node segments, by using a routing coordinator that executes an NFN execution plan, or by flooding an ICN-Route-Discovery-Request over multiple ICN route segments between first and second popular nodes, the second node selecting one of the ICN route segments and responding to the ICN-Route-Discovery-Request by sending a unicast Route-Discovery-Response to the first node over the selected one of the ICN route segments. Other methods for providing context aware forwarding for dynamic ICNs such as vehicular networks, RTT estimation for ICNs, and machine learning techniques for optimizing/compressing a forwarding information based in an ICN node are also provided.

Abstract: Methods are described for providing routing updates in information-centric networks (ICNs) by using a centralized ICN routing coordination unit to exchange updated routing tables with certain popular nodes in popular node segments, by using a routing coordinator that executes an NFN execution plan, or by flooding an ICN-Route-Discovery-Request over multiple ICN route segments between first and second popular nodes, the second node selecting one of the ICN route segments and responding to the ICN-Route-Discovery-Request by sending a unicast Route-Discovery-Response to the first node over the selected one of the ICN route segments. Other methods for providing context aware forwarding for dynamic ICNs such as vehicular networks, RTT estimation for ICNs, and machine learning techniques for optimizing/compressing a forwarding information based in an ICN node are also provided.

Abstract: Systems and techniques for information centric network (ICN) high definition (HD) map distribution are described herein. For example, a vehicle may detect a map tile event (e.g., moving into an area for which the vehicle does not have an up-to-date map tile). The vehicle may transmit an interest packet a name for the map tile via an ICN and receiving the map tile in a data packet sent in response to the interest packet.

Abstract: Described is a Logical Network Controller (LNC) operable to communicate with a User Equipment (UE) on a wireless network. The LNC may be operable to process connection request transmissions from the UE requesting a connection with an application service, such as a Mission-Critical Internet-of-Things (MC-IoT) service, to determine a Connection-specific Application Server Instance (CASI) for the application service, and to generate connection response transmissions for the UE carrying a connection-specific source IP address corresponding to the UE and a connection-specific destination IP address corresponding to the CASI.

Abstract: To address technical problems facing producer and consumer mobility in cellular ICN/NDN networks, a technical solution includes leveraging device tracking during handover in the cellular system to optimize cache replacement and route updates during handover. This solution also improves performance by advance caching and route update during mobility handling, which reduces or eliminates interest packet flooding and latency for upcoming potential content request and retrieval. This solution also improves performance by operating based on the observed popularity of the content, and based on the mobility patterns of the consumer and producer.