Disclosed herein are systems and methods for dynamically switching between synchronous and asynchronous communication channels. A communication request can be received from an application, and a request identifier can be generated for the communication request. The communication request can be transmitted to an edge server application via a first communication channel. The first communication channel can be selected from a plurality of communication channels based at least in part on a policy. In an instance in which a condition specified by the policy is detected in the transmission of the communication request, a second communication channel can be selected from the plurality of communication channels. The communication request can be transmitted to the edge server application using the second communication channel.

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.

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.

An apparatus for communication between a sending application and a receiving application of a receiving apparatus includes a processor that is configured to establish a stream for transmitting data between the sending application and the receiving application; receive a first request from the sending application to transmit metadata to the receiving application; receive a second request from the sending application to transmit application data to the receiving application; responsive to a determination that a frame that includes the application data and the metadata has a size that is smaller than or equal to a maximum frame size, construct the frame to include the application data and the metadata; and transmit the frame in a packet to the receiving apparatus.

The method is for the transfer of data of a message subdivided in fragments from a first intermediary electronic processing unit (43) to a second intermediary electronic processing unit (45); before the transfer, the first unit (43) receives the data encapsulated in the payload of data packets of the TCP type from a sender electronic processing unit (41) and decapsulates them; after the transfer, the second unit (45) encapsulates data in the payload of data packets of the TCP type and transmits them to a recipient electronic processing unit (47); the transfer takes place by means of data packets of the UDP type; the first unit (43) also inserts in the payload (32) of UDP packets; a first data field (C1) containing an identifier of a connection between the sender unit (41) and the recipient unit (47), a second data field (C2) containing an identifier of the message to be transferred, and a third data field (C3) containing a number that identifies the position of a fragment within the message to be transferred.

The invention relates to a method for distributing a network stream from at least one data source to a plurality of processors or processor cores of a computing device. The computing device has a network card which supports the receive side scaling (RSS) function, wherein, when this function is activated, the network card or its device driver generates an RSS indirection table (25) in which there is stored, for each index, the number of a processor or processor core, which will process an incoming data packet assigned to this index, and subsequently the network card calculates a hash value for each incoming data packet and maps the hash value to an index in precisely this table, wherein the hash value is formed via the combination of source and destination IP addresses and ports and is thus static for the duration of the connection. The method comprises the steps of specifying (34) at least one processor or processor core of the computing device, selecting (35) a port of the at least one data source, generating (36) a data set assigned to the selected port, determining (37) the processor or processor core assigned to the data set, repeating the steps of selection (35), generation (36) and determination (37) until a port has been determined for each specified processor or processor core, and sending (39) data packets via the ports determined for the specified processors or processor cores.

Systems for self-organizing data collection and storage in a refining environment are disclosed. An example system may include a swarm of mobile data collectors structured to interpret a plurality of sensor inputs from sensors in the refining environment, wherein the plurality of sensor inputs is configured to sense at least one of: an operational mode, a fault mode, a maintenance mode, or a health status of a plurality of refining system components disposed in the refining environment, and wherein the plurality of refining system components is structured to contribute, in part, to refining of a product. The self-organizing system organizes a swarm of mobile data collectors to collect data from the system components, and at least one of a storage operation of the data, a data collection operation of the sensors, or a selection operation of the plurality of sensor inputs.

Disclosed herein are various systems, apparatuses, software, and methods relating to data diode-TCP proxy with a User Datagram Protocol (UDP) across a wide area network (WAN) providing a WAN data diode using a uni-directional semantics protocol, providing a set of data diode proxies in either end of a point-to-point WAN link, providing a symmetric key encryption semantics to extend the WAN data diode securely across a WAN that is specified, wherein the symmetric key encryption semantics are implemented through the set of data diode proxies on either end of the point-to-point WAN link, employing a unidirectional protocol in communication transmitted using the WAN and, with data diode proxies, terminating one or more data channels on either end of the point-to-point WAN link or transporting a requisite information across the WAN over the uni-directional protocol.

Disclosed herein are various systems, apparatuses, software, and methods relating to data diode-TCP proxy with a User Datagram Protocol (UDP) across a wide area network (WAN) providing a WAN data diode using a uni-directional semantics protocol, providing a set of data diode proxies in either end of a point-to-point WAN link, providing a symmetric key encryption semantics to extend the WAN data diode securely across a WAN that is specified, wherein the symmetric key encryption semantics are implemented through the set of data diode proxies on either end of the point-to-point WAN link, employing a unidirectional protocol in communication transmitted using the WAN and, with data diode proxies, terminating one or more data channels on either end of the point-to-point WAN link or transporting a requisite information across the WAN over the uni-directional protocol.

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.