Abstract: A system described herein may record, to a distributed ledger, information associating a particular application with a particular set of Quality of Service (“QoS”) information. A particular Multi-Access/Mobile Edge Computing (“MEC”) device operator system may access the distributed ledger to identify the information associating the particular application with the particular set of QoS information. The system may read, from the distributed ledger, MEC configuration information indicating that the MEC device operator system has configured one or more MEC devices, of a plurality of MEC devices to provide the particular application in accordance with the particular set of QoS information. The system may select a particular MEC device, from the plurality of MEC devices, based on a request and further based on the MEC configuration information, and may output an indication of the selected particular MEC device in response to the request.

Abstract: In some implementations, a server device may receive a request to validate a connectivity between the server device and a device associated with a cellular site. The server device may generate an ISO image that includes site-specific configuration information for the cellular site. The server device may utilize the ISO image to configure an operating system of the device. The server device may test the connectivity between the server device and the device based on configuring the operating system. The server device may perform one or more actions based on testing the connectivity between the server device and the device.

Abstract: A system described herein may record, to a distributed ledger, information associating a particular application with a particular set of Quality of Service (“QoS”) information. A particular Multi-Access/Mobile Edge Computing (“MEC”) device operator system may access the distributed ledger to identify the information associating the particular application with the particular set of QoS information. The system may read, from the distributed ledger, MEC configuration information indicating that the MEC device operator system has configured one or more MEC devices, of a plurality of MEC devices to provide the particular application in accordance with the particular set of QoS information. The system may select a particular MEC device, from the plurality of MEC devices, based on a request and further based on the MEC configuration information, and may output an indication of the selected particular MEC device in response to the request.

Abstract: A system described herein may maintain first information associating Uniform Resource Locator (“URLs”) with respective Internet Protocol (“IP”) addresses of one or more edge computing devices. The system may maintain second information associating User Equipment (“UE”) identifiers with one or more locations. The system may receive a request, from a UE, including an identifier of the UE and a URL, may identify a location of the particular UE based on the identifier of the particular UE, and may compare the URL to the URLs included in the first information. The system may select a particular edge computing device based on the location of the particular UE, and may output, in response to the request, a particular IP address of the selected edge computing device.

Abstract: A system described herein may maintain records, in a distributed ledger, that include parameters (e.g., Quality of Service (“QoS”) parameters and/or Multi-Access/Mobile Edge Computing (“MEC”) device management parameters) that are associated with particular applications and/or MEC operator systems. The system may identify a particular record, from the distributed ledger, that is associated with a particular MEC operator system. The particular record may indicate a first set of MEC configuration parameters implemented by the MEC device operator system, and one or more triggers based on which the first set of MEC configuration parameters were implemented by the MEC device operator system. The system may record a set of modified application parameters, that are generated based on the identified first set of MEC configuration parameters and the one or more triggers, to the distributed ledger.

Abstract: A system described herein may maintain first information associating Uniform Resource Locator (“URLs”) with respective Internet Protocol (“IP”) addresses of one or more edge computing devices. The system may maintain second information associating User Equipment (“UE”) identifiers with one or more locations. The system may receive a request, from a UE, including an identifier of the UE and a URL, may identify a location of the particular UE based on the identifier of the particular UE, and may compare the URL to the URLs included in the first information. The system may select a particular edge computing device based on the location of the particular UE, and may output, in response to the request, a particular IP address of the selected edge computing device.

Abstract: 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.

Abstract: A system described herein may maintain records, in a distributed ledger, that include parameters (e.g., Quality of Service (“QoS”) parameters and/or Multi-Access/Mobile Edge Computing (“MEC”) device management parameters) that are associated with particular applications and/or MEC operator systems. The system may identify a particular record, from the distributed ledger, that is associated with a particular MEC operator system. The particular record may indicate a first set of MEC configuration parameters implemented by the MEC device operator system, and one or more triggers based on which the first set of MEC configuration parameters were implemented by the MEC device operator system. The system may record a set of modified application parameters, that are generated based on the identified first set of MEC configuration parameters and the one or more triggers, to the distributed ledger.

Abstract: A system described herein may record, to a distributed ledger, information associating a particular application with a particular set of Quality of Service (“QoS”) information. A particular Multi-Access/Mobile Edge Computing (“MEC”) device operator system may access the distributed ledger to identify the information associating the particular application with the particular set of QoS information. The system may read, from the distributed ledger, MEC configuration information indicating that the MEC device operator system has configured one or more MEC devices, of a plurality of MEC devices to provide the particular application in accordance with the particular set of QoS information. The system may select a particular MEC device, from the plurality of MEC devices, based on a request and further based on the MEC configuration information, and may output an indication of the selected particular MEC device in response to the request.

Abstract: 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.

Abstract: A device may include a memory storing instructions and processor configured to execute the instructions to receive, by a first blockchain node and via a first base station, a message from a first Internet of Things (IoT) device to a second IoT device, wherein the device corresponds to a first multi-access edge computing (MEC) device located in a first MEC network associated with the first base station. The processor may be further configured to authenticate, by the first blockchain node, the first IoT device using a blockchain associated with a group of IoT devices and send, by the first blockchain node, the message to a second blockchain node in a second MEC device in a second MEC network associated with a second base station servicing the second IoT device, in response to authenticating the first IoT device using the blockchain associated with the group of IoT devices.

Abstract: In some implementations, a server device may receive a request to validate a connectivity between the server device and a device associated with a cellular site. The server device may generate an ISO image that includes site-specific configuration information for the cellular site. The server device may utilize the ISO image to configure an operating system of the device. The server device may test the connectivity between the server device and the device based on configuring the operating system. The server device may perform one or more actions based on testing the connectivity between the server device and the device.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A device may include a memory storing instructions and processor configured to execute the instructions to receive, by a first blockchain node and via a first base station, a message from a first Internet of Things (IoT) device to a second IoT device, wherein the device corresponds to a first multi-access edge computing (MEC) device located in a first MEC network associated with the first base station. The processor may be further configured to authenticate, by the first blockchain node, the first IoT device using a blockchain associated with a group of IoT devices and send, by the first blockchain node, the message to a second blockchain node in a second MEC device in a second MEC network associated with a second base station servicing the second IoT device, in response to authenticating the first IoT device using the blockchain associated with the group of IoT devices.

Abstract: An example method described herein includes obtaining a private identifier for a private radio access network (RAN). The private identifier may be used by a user equipment (UE) to access the private RAN. The method may include deploying network functions to one or more devices of a private network platform. The network functions may be associated with one or more radio access technologies (RATs). The method may include configuring the private network platform to host the network functions to provide a private multi-access edge computing (MEC) environment. The private MEC environment may be configured to host one or more MEC applications. The method may include configuring a communication interface between the private RAN and the private MEC environment to enable the UE to access, via the private RAN, the private MEC environment and performing an action associated with the private MEC environment.

Abstract: 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.

Abstract: A device may include a memory storing instructions and processor configured to execute the instructions to receive, by a first blockchain node and via a first base station, a message from a first Internet of Things (IoT) device to a second IoT device, wherein the device corresponds to a first multi-access edge computing (MEC) device located in a first MEC network associated with the first base station. The processor may be further configured to authenticate, by the first blockchain node, the first IoT device using a blockchain associated with a group of IoT devices and send, by the first blockchain node, the message to a second blockchain node in a second MEC device in a second MEC network associated with a second base station servicing the second IoT device, in response to authenticating the first IoT device using the blockchain associated with the group of IoT devices.

Abstract: A method, a device, and a non-transitory storage medium are described in which a machine learning-based resource management service is provided. A network device obtains network and end device information, and uses machine learning to determine whether to adjust an auto-scaling rule pertaining to the provisioning of an application service. The network device generates a modified auto-scaling rule based on the analysis.