Fujitsu Corporation

Xi Wang

Paparao Palacharla

Qiong Zhang

Tadashi Ikeuchi

Motoyoshi Sekiya

Inwoong Kim

Nannan Wang

Takao Naito

Mukul Ranjan Prasad

Indradeep Ghosh

Qingya She

Chengyi Gao

Olga I Vassilieva

Martin Bouda

Weisheng Xie

Fredrick Gruman

Min He

Fan Yu

Mohammad Masud Hasan

Kevin Zhu

Qianqian Wang

Paparao Palacharia

Srinivas Vobilisetti

Qi Chen

Soroush Bateni

John David Campochiaro

Victor Mehmeri

Jian Kong

A method may include obtaining an image of a scene from a first perspective, the image including an object, and detecting the object in the image using a machine learning process, where the object may be representative of a known shape with at least four vertices at a first set of points. The method may also include automatically predicting a second set of points corresponding to the at least four vertices of the object in a second perspective of the scene based on the known shape of the object. The method may additionally include constructing, without user input, a transformation matrix to transform a given image from the first perspective to the second perspective based on the first set of points and the second set of points.

Automatic perspective transformation

Systems and methods including identifying a physical intelligent moving object (IMO), the physical IMO associated with a current location and a service request; creating, from a digital representation template that is based on the service request, a digital representation instance of the physical IMO in a particular edge cloud of a distributed cloud computing environment that is closest to the current location of the physical IMO; in response to creating the digital representation instance, establishing a network connection between the digital representation and the physical IMO using the particular edge cloud; detecting a movement of the physical IMO from coverage of the particular edge cloud; in response to detecting the movement of the physical IMO: identifying a target edge cloud of the distributed cloud computing environment for coverage of the physical IMO; and establishing a network connection between the digital representation and the physical IMO using the target edge cloud.

Digital representations of physical intelligent moving objects

Operations may include obtaining lists of inter-Network-Element connections (inter-NE connections) between connection points of different network elements included in a network and obtaining lists of internal connections of the network elements included in the list of inter-NE connections. The operations may also include generating, based on the lists of inter-NE connections and the lists of internal connections, a global list of connection points that correspond to the inter-NE connections and the internal connections. Moreover, the operations may include generating, based on the global list of connection points, a plurality of upstream connection chains and a plurality of downstream connection chains with respect to the internal connections. In addition, the operations may include generating a list of end-to-end circuits by combining the respective upstream connection chains and the respective downstream connection chains of each respective internal connection.

End-to-end circuit stitching

Systems and methods for identifying physical intelligent moving objects (IMOs); creating, for a first subset of the physical IMOs, digital representations in edge clouds of a distributed cloud computing environment, each digital representation representative of a physical IMO of the first subset of the physical IMOs; generating a cooperative network computing (CNC) platform that includes the digital representations of the first subset of the physical IMOs, each digital representation functioning as a CNC entity in the CNC platform for the corresponding physical IMO; identifying a CNC task of a first physical IMO of the plurality of physical IMOs; and performing, by a first digital representation of the representations that corresponds to the first physical IMO, the CNC task in the CNC platform, including accessing data associated with a second digital representation of the digital representations in the CNC platform to perform the CNC task at the first digital representation.

Edge-accelerated artificial intelligence for collaborative sensing of physical intelligent moving objects

Disclosed methods for network modernization include obtaining a list of end-to-end circuits carried in a circuit-switched network, calculating, for each circuit, an early retirement credit (ERC) score and a circuit load factor (CLF) score, selecting, dependent on the ERC and CLF scores, a circuit to migrate to a new network, adding the selected circuit to a circuit migration sequence, and removing the circuit from the list. The ERC score represents the number of circuit-switching units on which no circuits would be carried and that would remain in the network following its removal. The CLF score represents an average number of circuits that would be carried on each circuit-switching unit currently traversed by the circuit following its removal. When two circuits have the highest ERC score, the circuit with the lowest CLF score is selected for migration. The method is repeated until the list is empty.

Circuit migration sequence generation for network modernization

Systems and methods for provisioning real-time three-dimensional maps, including: at a first processing stage: updating a three-dimensional map of an environment based on received point cloud data; extracting three-dimensional proposals of objects of the environment; projecting the three-dimensional proposals onto a two-dimensional image of the environment; generating two-dimensional proposals of the objects of the environment; at a second processing stage: detecting the objects of the environment from the two-dimensional image of the environment; generating two-dimensional bounding boxes of the objects of the environment; matching the two-dimensional bounding box with a particular two-dimensional proposal of the two-dimensional proposals; and labeling, for each two-dimensional proposal that is matched to a two-dimensional bounding box, the three-dimensional proposal corresponding to the two-dimensional proposal with semantic information associated with the two-dimensional bounding box that is matched to the two-dimensional proposal to update the three-dimensional map.

Provisioning real-time three-dimensional maps for autonomous vehicles

Systems and methods for transmitting, within a time slot, i) first eMBB resource blocks to a first UE and ii) second eMBB resource blocks to a second UE; during transmission of the first and the second eMBB resource blocks to the first and the second UE, respectively, at a first scheduled check point: identifying i) first URLLC resource blocks to be transmitted to a third UE and ii) second URLLC resource blocks to be transmitted to a fourth UE; identifying i) a first transmission deadline for transmitting the first URLLC resource blocks to the third UE and ii) a second transmission deadline for transmitting the second URLLC resource blocks to the fourth UE; generating a transmission queue for the first URLLC resource blocks and the second URLLC resource blocks; and selecting, based on the transmission queue, the second URLLC resource blocks for transmission to the fourth UE.

Multiplexing of resource blocks within a communications network for dynamic service provisioning

Systems and methods for mapping service function chains to physical network resources include receiving a service function chain request specifying multiple service functions including a service access point, generating a service graph including service links between consecutive service functions, receiving resource information describing capabilities of physical network resources and a topology of the physical network, generating a resource graph including infra links between pairs of connected physical network resources, creating, dependent on the service graph and the resource graph, multiple solutions for mapping the service functions to the physical network resources, and outputting one or more mapping solutions. Each of generating the service graph, generating the resource graph, and creating the mapping solutions may be performed by one or instances of respective microservices that operate in parallel. The systems may also include respective microservice instances for creating end point mappings, creating infra node mappings, and pruning and ranking mapping solutions.

Service function chain mapping using multiple parallel microservices instances

An intersection management system (IMS) may receive one or more traversing requests from one or more Connected Autonomous Vehicles (CAVs). The IMS may determine a solution space for each of the one or more traversing requests in a space-time resource model of the intersection, find a CAV trajectory allocation in the space-time resource model for each of the one or more traversing requests. The IMS may send an approved reservation to each CAV corresponding to each of the one or more CAV trajectory allocations that have been found. Each of the one or more CAVs may, when an approved reservation corresponding to the CAV may have been received from the IMS, move through the intersection zone as specified in the approved reservation.

Fragmentation-aware intelligent autonomous intersection management using a space-time resource model

Systems and methods for identifying a service region that includes sub-regions; calculating, for each pair of neighboring sub-regions, traffic data of computing devices traveling between the pair of sub-region; generating a directed graph representing the service region, the directed graph including nodes representing the sub-regions and the links between the nodes representing the first and the second traffic data; partitioning the directed graph into graph partitions, each graph partition including sub-graphs; calculating, for each sub-graph of each graph partition, a net traffic flow for the sub-graph based on a difference of the first and the second traffic data of the sub-regions that correspond to the nodes of the sub-graph; calculating, for each graph partition, a net traffic flow for the graph partition based on a summation of the net traffic flow of each sub-graph of the graph partition; identifying a particular graph partition having a smallest net traffic flow.

Distribution of computing resources of a radio access network

Systems and methods for traffic congestion avoidance may use cooperative autonomous driving based on vehicle-to-vehicle communication to resolve deadlock conditions. The method may include automatically detecting, by a given autonomous vehicle, that the given vehicle is deadlocked, initiating, by the given vehicle, formation of a coordination group including the given vehicle, a front vehicle traveling in the same driving lane as the given vehicle, and an assistant autonomous vehicle traveling in a lane adjacent to the lane in which the given vehicle and the front vehicle are traveling, and sending, by the given vehicle using vehicle-to-vehicle communication, a cooperative driving task request to initiate actions by the autonomous vehicles in the coordination group to resolve the deadlock condition. The actions may include modifying a driving plan of an autonomous vehicle in the coordination group and initiating a speed negotiation with an autonomous vehicle in the coordination group.

Cooperative autonomous driving for traffic congestion avoidance

Systems and methods for identifying a mapping solution for a virtual network request are disclosed. A resource orchestrator may receive a virtual network request specifying resources required on physical nodes in a network and generate a mapping solution for the request. Generating the mapping solution may include identifying vertices at which a first resource is available, mapping each identified vertex to the first resource in a respective candidate chaining solution, determining, for each identified vertex, a number of messages including the candidate chaining solution to be forwarded to respective neighbor vertices, and forwarding the determined number of messages to the respective neighbor vertices. Determining the number of messages to be forwarded may include applying a message forwarding policy to reduce the total number of messages forwarded between vertices when generating the mapping solution. The policy may be dependent on the topology of the virtual network request.

Efficient message forwarding for distributed resource orchestration

Systems and methods for identifying a pair of nodes of a plurality of nodes of a virtual optical network (VON); identifying i) an optical route between the pair of nodes and ii) a desired availability of the optical route; determining a probability density function (PDF) of a signal-to-noise ratio (SNR) of a signal of the optical route; determining a SNR threshold such that an integration of the PDF of the SNR of the signal above the SNR threshold corresponds to the desired availability of the optical route; determining a plurality of spectral efficiencies that corresponds to the SNR threshold, each spectral efficiency of the plurality of spectral efficiencies associated with a respective modulation format of a plurality of modulation formats; and identifying a particular modulation format of the plurality of modulation formats that corresponds to a maximum spectral efficiency of the plurality of spectral efficiencies.

Method and system for assigning modulation format in optical networks

A method for VON service with guaranteed availability may use probability density functions (PDF) of Q-factor to determine availability of physical links assigned to a virtual link in the VON. Then, a VON mapping may be performed based on the determined availabilities, among other factors.

Virtual optical network service with guaranteed availability

A control system for spectral slot assignment in flexible grid optical networks determines, for a given optical path, a physical source node, a physical destination node, and physical intermediate nodes, determines the number of contiguous spectral slots to allocate for traffic on the path, identifies candidate combinations of spectral slots available for the traffic, and creates an auxiliary graph for the path. The auxiliary graph includes auxiliary links representing candidate combinations of spectral slots, virtual nodes representing pairs of neighboring physical nodes, and auxiliary links between each pair of virtual source-side and destination-side intermediate nodes representing either pass-through traffic or wavelength shifted traffic. The control system assigns cost values to the auxiliary links, determines a lowest cost combination of auxiliary links from the source to the destination, allocates the corresponding candidate combinations of spectral slots to the traffic, and configures the physical intermediate nodes accordingly.

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Murphy, TX, United States of America

Xi Wang