The present disclosure relates to a transmitting device and a transmitting method, and a receiving device and a receiving method which are capable of improving confidentiality and communication resistance in low power wide area (LPWA) communication. The transmitting device generates a key stream on the basis of GPS time information, encrypts transmitted data on the basis of the key stream to generate encrypted data, and transmits the encrypted data to the receiving device. The receiving device generates a key stream on the basis of GPS time information and decodes the encrypted data into the transmitted data on the basis of the key stream. The present disclosure can be applied to an LPWA communication system.

The present disclosure relates to a transmitting device and a transmitting method, and a receiving device and a receiving method which are capable of improving confidentiality and communication resistance in low power wide area (LPWA) communication. The transmitting device generates a key stream on the basis of GPS time information, encrypts transmitted data on the basis of the key stream to generate encrypted data, and transmits the encrypted data to the receiving device. The receiving device generates a key stream on the basis of GPS time information and decodes the encrypted data into the transmitted data on the basis of the key stream. The present disclosure can be applied to an LPWA communication system.

First sensor data can be received from a first set of IoT devices. Sensor data collection rates can be determined for a first artificial intelligence model by analyzing the first sensor data using a second artificial intelligence model. Based on the sensor data collection rates, sensor control commands can be communicated to a second set of Internet of Things devices. The sensor control commands can specify, to the second set of Internet of Things devices, sensor data communication rates that respective ones of the second set of Internet of Things devices are to implement for communicating, to the first artificial intelligence model, second sensor data generated by sensors of the respective ones of the second set of Internet of Things devices.

First sensor data can be received from a first set of IoT devices. Sensor data collection rates can be determined for a first artificial intelligence model by analyzing the first sensor data using a second artificial intelligence model. Based on the sensor data collection rates, sensor control commands can be communicated to a second set of Internet of Things devices. The sensor control commands can specify, to the second set of Internet of Things devices, sensor data communication rates that respective ones of the second set of Internet of Things devices are to implement for communicating, to the first artificial intelligence model, second sensor data generated by sensors of the respective ones of the second set of Internet of Things devices.

The present disclosure relates to a system comprising an alarm management module (AMM) that receives an alarm raised by an application running on a network function virtualization unit (NFVU) infrastructure, said NFVU infrastructure comprising a virtualization layer; and facilitates enrichment of the received alarm with NFVU infrastructure specific information based on a physical-and-virtual inventory associated with the NFVU infrastructure, said NFVU infrastructure specific information pertaining to hardware and virtual resources of the NFVU infrastructure that are involved in running said application. The AMM can further receive an infrastructure alarm pertaining to a hardware resource that forms part of the NFVU infrastructure, said infrastructure alarm being associated with a failure of or a potential functional error of the hardware resource; and facilitate enrichment of the received infrastructure alarm information with application information, said application information pertaining to at least one application that is impacted by the hardware resource.

Enablement of a voice channel being established between an IoT device and a controller through the use of a voice-line service system.

Enablement of a voice channel being established between an IoT device and a controller through the use of a voice-line service system.

A traffic analysis apparatus includes: a first means that estimates a state sequence from time-series data of communication traffic based on a hidden Markov model, and groups, into one group, a plurality of patterns with resembling state transitions in the state sequence to perform extraction of a state sequence, with taking the plurality of patterns grouped into one group as one state; and a second means that determines an application state corresponding to the time-series data based on the state sequence extracted by the first means and predetermined application characteristics.

Disclosed are a method and devices for determining a location context of a first device. The method includes receiving, at the first device, a wireless signal from a second device, determining a proximity of the first device to the second device based on the wireless signal, and determining an area inference based on characteristics of the second device and based on the determined proximity of the first device to the second device. The area inference includes a category of the area. The method also includes assigning an area label to the first device based on the area inference, and providing the area label to an application to enhance the performance of the application.

Provided herein are systems and methods for implementing a network consensus for a blockchain network that is characterized by one or more, or all, of the following attributes: (1) implementation of a Proof-of-Coverage scheme; (2) lack of permission for nodes to participate in the network; (3) decentralization, with lack of incentives to centralize; (4) byzantine fault tolerance; (5) based on useful work to the network; (6) high confirmed transaction rate; and (7) censor-resistant transactions.