Abstract: Presented herein are methodologies for implementing a system and apparatus to estimate a network disruption index and undertake a mitigation action accordingly. A method includes calculating a network disruption index based on at least a disruption score associated with a service request measure, an end-of-life measure, a security incident response measure and a return material authorization measure for respective hardware devices in a network, comparing the network disruption index to a predetermined threshold, and when the network disruption index is above the predetermined threshold, identifying one or more of the hardware devices in the network for a mitigation action and implementing the mitigation action.

Abstract: The present technology addresses a need in the art for an automated tool that allows users to create network-based custom workflows for networks and associated management applications. The users do not need to have in-depth network knowledge to work with the tool or even write any code/script. The tool provides the users with a flexible graphical user interface for automated troubleshooting, network provisioning, and closed-loop automation. Further, the tool uses a domain-independent semantic machine reasoning engine as an underlying engine and a mock data engine to test and validate network-based workflows created by the users.

Abstract: The present technology addresses a need in the art for a closed-loop automation system of a managed network that detects and fixes an issue in the managed network with minimal to no human intervention. The closed-loop automation system employs a domain-independent semantic machine reasoning engine as an underlying engine. After detecting the issue in the managed network, the system searches through a knowledge base to find a match for the detected issue. The knowledge base includes previously collected knowledge from subject matter experts and maintenance teams. The system then proposes a remedial action to a user of the managed network for approval. After approval by the user, the system implements the remedial action.

Abstract: The present technology addresses a need in the art for an automated tool that allows users to create network-based custom workflows for networks and associated management applications. The users do not need to have in-depth network knowledge to work with the tool or even write any code/script. The tool provides the users with a flexible graphical user interface for automated troubleshooting, network provisioning, and closed-loop automation. Further, the tool uses a domain-independent semantic machine reasoning engine as an underlying engine and a mock data engine to test and validate network-based workflows created by the users.

Abstract: The present technology addresses a need in the art for a closed-loop automation system of a managed network that detects and fixes an issue in the managed network with minimal to no human intervention. The closed-loop automation system employs a domain-independent semantic machine reasoning engine as an underlying engine. After detecting the issue in the managed network, the system searches through a knowledge base to find a match for the detected issue. The knowledge base includes previously collected knowledge from subject matter experts and maintenance teams. The system then proposes a remedial action to a user of the managed network for approval. After approval by the user, the system implements the remedial action.

Abstract: The present technology addresses a need in the art for an automated tool that allows users to create network-based custom workflows for networks and associated management applications. The users do not need to have in-depth network knowledge to work with the tool or even write any code/script. The tool provides the users with a flexible graphical user interface for automated troubleshooting, network provisioning, and closed-loop automation. Further, the tool uses a domain-independent semantic machine reasoning engine as an underlying engine and a mock data engine to test and validate network-based workflows created by the users.

Abstract: Presented herein are methodologies for implementing a system and apparatus to estimate a network disruption index and undertake a mitigation action accordingly. A method includes calculating a network disruption index based on at least a disruption score associated with a service request measure, an end-of-life measure, a security incident response measure and a return material authorization measure for respective hardware devices in a network, comparing the network disruption index to a predetermined threshold, and when the network disruption index is above the predetermined threshold, identifying one or more of the hardware devices in the network for a mitigation action and implementing the mitigation action.

Abstract: Various implementations disclosed herein enable blockchain programming in NB-IoT devices. In various implementations, a method of blockchain authentication is performed by a computing device including one or more processors, and a non-transitory memory. In various implementations, the method includes maintaining a blockchain for a machine-to-machine network, wherein the machine-to-machine network is a narrowband internet of things network. In some implementations, the method includes receiving a request for a first set of data from the blockchain by a second device. In some implementations, the method includes determining based on the request, the first set of data from the blockchain by traversing a series of blocks from the blockchain. In some implementations, the method includes packaging the first set of data from the blockchain according to a protocol into a packaged data unit and transmitting the packaged data unit to the second device.

Abstract: Presented herein are methodologies for implementing a system and apparatus to estimate a network disruption index and undertake a mitigation action accordingly. A method includes calculating a network disruption index based on at least a disruption score associated with a service request measure, an end-of-life measure, a security incident response measure and a return material authorization measure for respective hardware devices in a network, comparing the network disruption index to a predetermined threshold, and when the network disruption index is above the predetermined threshold, identifying one or more of the hardware devices in the network for a mitigation action and implementing the mitigation action.

Abstract: In one embodiment, a processor receives data indicative of a plurality of conversations involving a primary user. The processor identifies a subset of the plurality of conversations that are regarding a particular topic. The processor adds a conversation to the subset based on a match between one or more keywords in the conversation matching a list of keywords associated with the particular topic. The processor uses a machine learning-based model to identify one or more context characteristics of the conversations in the identified subset. The processor updates the subset of conversations by adding at least one of the conversations to the subset based on the at least one conversation having at least one context characteristic identified by the machine learning-based model. The processor provides data indicative of the updated subset of conversations to a user interface for review by the primary user.

Abstract: A network function (NF) entity in a communication network receives authentication data associated with a User Equipment (UE), determines the UE supports a blockchain registration procedure based on the authentication data, exchanges authentication messages with a Blockchain Roaming Broker (BRB) entity over a blockchain network interface, receives a blockchain authentication confirmation from the BRB entity, and registers the UE with the core network based on the blockchain authentication confirmation.

Abstract: A Network Function (NF) entity in a telecommunication network receives blockchain credentials associated with UE and selects a Blockchain Charging Function (BCF). The NF entity further generates a Charging Data Record (CDR) corresponding to network resources, and sends a charging request based on the CDR (and policy rules) to the BCF entity over a blockchain network interface. The BCF entity sends a confirmation of the charging request, and the NF entity, based on the confirmation, provisions the network resources to the UE.

Abstract: Presented herein are methodologies for implementing a system and apparatus to estimate a network disruption index and undertake a mitigation action accordingly. A method includes calculating a network disruption index based on at least a disruption score associated with a service request measure, an end-of-life measure, a security incident response measure and a return material authorization measure for respective hardware devices in a network, comparing the network disruption index to a predetermined threshold, and when the network disruption index is above the predetermined threshold, identifying one or more of the hardware devices in the network for a mitigation action and implementing the mitigation action.

Abstract: A network function (NF) entity in a communication network receives authentication data associated with a User Equipment (UE), determines the UE supports a blockchain registration procedure based on the authentication data, exchanges authentication messages with a Blockchain Roaming Broker (BRB) entity over a blockchain network interface, receives a blockchain authentication confirmation from the BRB entity, and registers the UE with the core network based on the blockchain authentication confirmation.

Abstract: A Network Function (NF) entity in a telecommunication network receives blockchain credentials associated with UE and selects a Blockchain Charging Function (BCF). The NF entity further generates a Charging Data Record (CDR) corresponding to network resources, and sends a charging request based on the CDR (and policy rules) to the BCF entity over a blockchain network interface. The BCF entity sends a confirmation of the charging request, and the NF entity, based on the confirmation, provisions the network resources to the UE.

Abstract: Various implementations disclosed herein enable blockchain programming in NB-IoT devices. In various implementations, a method of blockchain authentication is performed by a computing device including one or more processors, and a non-transitory memory. In various implementations, the method includes maintaining a blockchain for a machine-to-machine network, wherein the machine-to-machine network is a narrowband internet of things network. In some implementations, the method includes receiving a request for a first set of data from the blockchain by a second device. In some implementations, the method includes determining based on the request, the first set of data from the blockchain by traversing a series of blocks from the blockchain. In some implementations, the method includes packaging the first set of data from the blockchain according to a protocol into a packaged data unit and transmitting the packaged data unit to the second device.

Abstract: A network function (NF) entity in a communication network determines a User Equipment (UE) supports a blockchain authentication procedure, exchanges authentication messages with a Blockchain Authentication Function (BAF) entity over a blockchain network interface (e.g., based on the blockchain authentication procedure), receives a blockchain authentication confirmation from the BAF entity, and registers the UE based on the blockchain authentication confirmation.

Abstract: A network function (NF) entity in a communication network receives session request data associated with a User Equipment (UE), which includes blockchain authentication data. The NF entity selects a Blockchain Authentication Function (BAF) entity based on the session request data, and exchanges at least a portion of the blockchain authentication data with the BAF entity over a blockchain network interface. The NF entity further receives authentication confirmation data from the BAF entity over the blockchain network interface, and establishes a data session associated with the UE based on the authentication confirmation data.

Abstract: A network function (NF) entity in a communication network determines a User Equipment (UE) supports a blockchain authentication procedure, exchanges authentication messages with a Blockchain Authentication Function (BAF) entity over a blockchain network interface (e.g., based on the blockchain authentication procedure), receives a blockchain authentication confirmation from the BAF entity, and registers the UE based on the blockchain authentication confirmation.

Abstract: A network function (NF) entity in a communication network receives session request data associated with a User Equipment (UE), which includes blockchain authentication data. The NF entity selects a Blockchain Authentication Function (BAF) entity based on the session request data, and exchanges at least a portion of the blockchain authentication data with the BAF entity over a blockchain network interface. The NF entity further receives authentication confirmation data from the BAF entity over the blockchain network interface, and establishes a data session associated with the UE based on the authentication confirmation data.