A first network device for use in a blockchain network is described. The first network device comprises means for, while carrying out a first iteration of a consensus protocol involving a second node device (103), in response to a trigger event (3040), obtaining a time interval function of a time interval start trigger event (3040) and of a time interval end trigger event (3080), each event being linked to a message of the consensus protocol and wherein at least the end trigger event (3080) comprises receiving a message from the second node device; means for transmitting (3083) first data (Delay_102) representative of said time interval to said second node device; means for, during a subsequent iteration of said consensus protocol involving said second node device, receiving a message (3140) from said second node device, said message containing second data (DelayTX_102) representative of said time interval from said second node device; means for authenticating said second node device as a function of said second data. A second network device, methods at the first and second network devices and a computer readable medium with code for carrying out the methods are also described.

An instructing computing device (210) is disclosed that is operable to implement a 5Constrained Application Protocol (CoAP). The computing device comprises processing circuitry configured to send a first message (211) to a target computing device (220), which comprises a first message identifier and store a record (212) of the first message in a memory. The processing circuitry is further configured to receive a second message (223) from the target computing device, the second message confirming that 0the target computing device has received the first message, wherein the first message is configured to cause the target computing device to store a record (222) of the first message.

The present application discloses a data processing method and apparatus for performing protocol parsing in the cloud. A specific implementation of the method includes: acquiring a slave station data reading rule table that is configured by a user in the cloud; downloading the slave station data reading rule table to a gateway in a slave station; receiving slave station data that is associated with the slave station and that is read by the gateway according to the slave station data reading rule table; parsing the slave station data according to a parsing table in the cloud preset by the user; and processing the parsed slave station data. This implementation implements the processing of data of different communication protocols in the cloud.

Various techniques can include accessing a master tree that was generated using a plurality of protocol definitions. The plurality of protocol definitions can identifies an ordered set of actions and specifies, for each sequential pair of actions in the ordered set of actions, an action-advancement condition that identifies a criterion for advancing across the sequential pair of actions in the ordered set of actions so as to trigger a later of the sequential pair of actions. A master tree includes a set of dynamic nodes and a set of static nodes. The technique can include accessing a partial protocol definition that includes at least one action. The technique can include generating an auto-completion of the partial protocol definition using the master tree, at least some of the dynamic-node weights, and at least some of the static-node weights. The technique can output a representation of an auto-completed protocol definition.

The invention relates to a computer-implemented method for exchanging information, through a DAG/Hashgraph consensus algorithm via a gossip protocol, the method includes making a first given node select a second given node randomly and send reference information; determining based on the reference information which node events are in front of that of the others; if the reference information implies that the events of the first given node is in front of that of the second given node, then sending a cancellation information to the first given node, preventing, in consequence, the first given node from sending DAG-event information to the second given node; if the reference information implies that the events of the second given node is in front of that of the first given node, then making the first given node send DAG-event information to the second given node; and soon through the network.

Systems, methods, and machine-readable media for processing data transmissions from a plurality of client devices to create composites for transmission to destination addresses are provided. Communications via a network may be received from a set of devices. Each communication may include a digital identifier corresponding to a destination specification. The communication may be processed to identify the digital identifier and to identify the destination specification. A data portion may be selected from the communication and cached. A second format may be identified as corresponding to a second communication medium, where the second format is different from a first format of the communication. A composite may be created according to the second format. The composite may include the selected data portion and the destination specification. The composite formatted according to the second format may be transmitted toward an endpoint device in accordance with the destination specification.

The present disclosure relates to a method, device and computer program for communicating information relating to wireless power transmission, and a recording medium thereof. A quick discovery method by means of out-of-band (OOB) in a wireless power transmission system according to an embodiment of the present disclosure can comprise the steps in which: a power transmitter (PTX) receives one or more advertisement data items from a power receiver (PRX) in the OOB; the PTX obtains a first service or characteristic of the PRX in the OOB on the basis of the advertisement data items; power transmission from the PTX to the PRX is initiated in-band on the basis of the first service or characteristic; and the PTX obtains a second service or characteristic of the PRX in the OOB after the power transmission has been initiated.

A technology is provided for invoking a random linear network coding (RLNC) communications protocol between a client and server in a network. In one example, a synchronize message requesting a network connection to a server can contain an indication that a client supports the RLNC communications protocol to encode and decode data packets using random linear network coding. The server can analyze the synchronize message for the indication that the client supports the RLNC communications protocol and send an acknowledge message to the client indicating that the server supports the RLNC communications protocol. Thereafter, the server can listen on a communications channel for a connection request sent by the client to communicate with the server using the RLNC communications protocol.

This application provides a data transmission method and apparatus, and relates to the field of communications technologies. The method includes: obtaining a plurality of code block streams; distributing, based on a preset multiplexing sequence, code blocks in the plurality of code block streams by slots, to form a single, interleaved code block stream from the plurality of code block streams; and segmenting and encapsulating the single, interleaved code block stream, to generate at least one frame. By utilizing time division duplexing techniques, a data transmission delay of the code block streams can be reduced.

Systems and methods are disclosed to infer, using a machine learned model, a service protocol of a server based on the banner data produced by the server. In embodiments, the machine learned model is implemented by a network scanner configured to receive banner data from open ports on servers. A received banner is parsed into a set of features, such as the counts or presence of particular characters or strings in the banner. In embodiments, certain types of banner content such as network addresses, hostnames, dates, and times, are replaced with special characters. The machine learned model is applied to the features to infer a most likely protocol of the server port that produced the banner. Advantageously, the model can be trained to perform the inference task with high accuracy and without using human-specified rules, which can be brittle for unconventional banner data and carry undesired biases.