Verizon Patent and Licensing Inc.

Other

Kirk Campbell

Raghuram Parvataneni

Anil Krishna Guntupalli

Ravi K Sharma

Sivanaga Ravi Kumar Chunduru Venkata

John Patrick Hickey, Iii

Art Zaifman

Manish Srivastava

Patricia Ruey Chang

Fred Weisbrod

Raghu Rami Reddy Valisammagari

Parry Cornell Booker

Maqbool Chauhan

Jerry Steben

David Taft

Niranjan B Avula

David Lindel Harris

Srinivasa M Kalapala

Anthony Mathias George

Ajaykumar Kalla

Eric T Handley

Chad Allenbrand

Edward G Leyton

Anthony Sirignano

Jayashree Srinivasan Kilkovalavedu

Richard J Campbell, Jr

A device may include a processor configured to determine a plurality of requirements for a Multi-Access Edge Computing (MEC) application requested by a customer; select a solution blueprint for the MEC application, from a set of solution blueprints, based on the determined plurality of requirements, wherein the solution blueprint includes an application deployment blueprint and a connectivity blueprint; and receive approval of the selected solution blueprint from the customer. The processor may be further configured to configure at least one transport network device based on the connectivity blueprint, in response to receiving the approval of the selected solution blueprint from the customer; and deploy at least one component of the MEC application on a MEC device in a MEC network based on the application deployment blueprint, in response to receiving the approval of the selected solution blueprint from the customer.

Systems and methods for configuring and deploying multi-access edge computing applications

Systems and methods described herein provide a co-managed configuration service. A network device stores parameters for the co-managed configuration service. The parameters identify exposed services for an enterprise network that uses devices from a network service provider. The network device receives, via a customer portal, a vendor-agnostic change request for the enterprise network. The change request includes a user role and a change request name for one of the exposed services. The network device authenticates the change request based on the user role and the change request name and retrieves vendor director information for an SDN device implementing the configuration change. The network device invokes, in response to the change request, the configuration change for the enterprise network based on the vendor director information.

Software defined network device exposure to third parties

A method, a device, and a non-transitory storage medium are described in which an application layer network management service is provided. The service may allow third parties associated with an application layer network to develop and on-board application-aware logic that manages application services. The application-aware logic may include optimization of the application service and remedial procedures that address events associated with degradation and/or performance of the application service. The application-aware logic may be implemented in conjunction with other logic provisioned by a network provider.

Method and system for application service management

A computer device may include a memory storing instructions and processor configured to execute the instructions to provide a test configuration to a plurality of multi-access edge computing (MEC) devices; collect test results associated with the provided test configuration from the plurality of MEC devices; and obtain capability information associated with particular ones of the plurality of MEC devices. The computer device may be further configured to generate a test report that relates one or more parameters included in the test results and the obtained capability information to particular ones of the plurality of MEC devices; and use the generated test report to select a MEC device from the plurality of MEC devices for a user equipment (UE) device requesting an application session.

Systems and methods for monitoring performance in distributed edge computing networks

A device may receive historical network behavior data associated with a network that includes network devices and may receive historical weather data associated with a geographical location of the network. The device may receive historical action data identifying historical actions taken for the network in response to the historical weather data, and may train a correlation model, with the historical network behavior data, the historical weather data, and the historical action data, to generate a trained correlation model. The device may receive a weather event forecast associated with the geographical location, and may process the weather event forecast, with the trained correlation model, to determine an anticipated behavior of the network in response to the weather event forecast. The device may process data identifying the anticipated behavior, with the trained correlation model, to identify actions to take in response to the anticipated behavior and may perform the actions.

Systems and methods for optimizing a network based on weather events

An illustrative latency service system identifies, in response to a request by a user equipment (UE) device for performance of a distributed computing service, a latency performance level to which the UE device is subscribed. The system obtains real-time latency performance data for a distributed computing network that is to perform the distributed computing service for the UE device in response to the request, and, based on the real-time latency performance data, determines a characteristic of a geographic zone in which the UE device is located. The characteristic is associated with latency performance that the distributed computing network is capable of providing in the geographic zone. Based on the latency performance level and the characteristic of the geographic zone, the system arranges for the performance of the distributed computing service for the UE device by the distributed computing network. Corresponding methods and systems are also disclosed.

Methods and systems for orchestrating a distributed computing service based on latency performance levels

An exemplary edge compute orchestration system that is communicatively coupled with a set of edge compute nodes in a communication network accesses performance data aggregated by a particular edge compute node of the set. The performance data includes a performance metric and geolocation data detected by a user equipment (UE) device communicatively coupled to the communication network. The edge compute orchestration system integrates the performance data into a geolocation-indexed performance dataset representative of detected performance metrics, indexed by geolocation, for the communication network. Then, based on the geolocation-indexed performance dataset, the edge compute orchestration system selects the particular edge compute node for performance of an edge compute task. Corresponding systems and methods are also disclosed.

Methods and systems for multi-access edge compute node selection based on a geolocation-indexed performance dataset

A device receives, from a first compute instance, a Remote Latency Call, that includes a target latency measure, a function, and one or more arguments for the function. The device clusters a plurality of compute instances into multiple clusters of compute instances based on a respective latency measure associated with each compute instance of the plurality of compute instances, and determines a first cluster of compute instances from the multiple clusters of compute instances that satisfies the target latency measure. The device causes a second compute instance within the first cluster of compute instances to execute the function, using the one or more arguments, and return one or more results.

Remote latency calls for latency clustered compute instances

An illustrative multi-access server orchestration system determines a subset of a set of multi-access servers associated with a communication network. The subset corresponds to a service area of a network anchor point through which network traffic on the communication network is routed to a client device. The multi-access server orchestration system orders the multi-access servers included within the subset to form an ordered listing of multi-access servers from a most-preferred to a least-preferred multi-access server for fulfilling a service request for the client device. The ordered listing designates a first multi-access server included in the subset and located more proximate to the network anchor point than to the client device to be more highly preferred for fulfilling the service request than a second multi-access server included in the subset and located more proximate to the client device than to the network anchor point. Corresponding methods and systems are also disclosed.

Methods and systems for multi-access server orchestration

A system described herein may provide a technique for the dynamic selection of configurable resources in an environment that includes a hierarchical or otherwise differentiated arrangement of configurable resources. The environment may include, or may be implemented by, a Distributed Resource Network ('DRN'), which may include hardware or virtual resources that may be configured, including the instantiation of containers, virtual machines, Virtualized Network Functions ('VNFs'), or the like. The DRN may be hierarchical in that some resources of the DRN may provide services to, and/or may otherwise be accessible to, a greater quantity of elements of the DRN or some other network.

Systems and methods for dynamically allocating resources based on configurable resource priority

A packet destined for a Multi-access Edge Computing (MEC) network is received at a wireless station from a user device. A serving gateway (SGW) receives the packet from the wireless station via an S1U GTP tunnel and assigns an uplink S1U General Packet Radio Service (GPRS) Tunneling Protocol (GTP) tunnel endpoint identifier (TEID) to the packet. The SGW performs a network address translation (NAT) function on the packet based on the uplink S1U GTP TEID assigned to the packet to form a translated packet. The SGW transmits the translated packet to the MEC network.

Systems and methods for network address translation

Systems and methods described herein provide an assisted network change service. A network device stores a record of network resources for a customer network and generates, based on the record, a visual representation of the network topology for a selected site of the customer network. The network device receives, from the customer, input for a change to configuration parameters of one of the network resources and verifies if the change to the configuration parameters is compatible with other settings in the customer network. When the change to the configuration parameters is compatible with other settings in the customer network, the network device generates a change request based on the configuration parameters and invokes provisioning to implement the change request for the customer network.

Assisted and context-driven network changes

Systems and methods provide a MEC policy optimization service. A network device applies, in a first edge cluster of the application service layer network, a policy for an application service that supports a customer application; receives network performance data related to execution of the application service; identifies, based on the network performance data, an improved policy to optimize the first policy for the customer application in the first edge cluster; and sends a model of the improved policy to a central network device for the application service layer network.

System and methods for service policy optimization for multi-access edge computing services

A device receives, from a first compute instance, a Remote Latency Call, that includes a target round trip time (RTT), a function, and one or more arguments for the function. The device determines, responsive to the Remote Latency Call, a first cluster of compute instances that satisfies the target RTT. The device migrates code associated with the function to a second compute instance within the first cluster of compute instances, and passes the arguments to the second compute instance for execution of the function.

Growing community of inventors

Long Valley, NJ, United States of America

Kirk Campbell