The invention provides, in one aspect, an improved system for data access comprising a file server that is coupled to a client device or application executing thereon via one or more networks. The server comprises static storage that is organized in one or more directories, each containing, zero, one or more files. The server also comprises a file system operable, in cooperation with a file system on the client device, to provide authorized applications executing on the client device access to those directories and/or files. Fast file server (FFS) software or other functionality executing on or in connection with the server responds to requests received from the client by transferring requested data to the client device over multiple network pathways. That data can comprise, for example, directory trees, files (or portions thereof), and so forth.

Systems and techniques for distributed machine learning (DML) in an information centric network (ICN) are described herein. Finite message exchanges, such as those used in many DML exercises, may be efficiently implemented by treating certain data packets as interest packets to reduce overall network overhead when performing the finite message exchange. Further, network efficiency in DML may be improved achieved by using local coordinating nodes to manage devices participating in a distributed machine learning exercise. Additionally, modifying a round of DML training to accommodate available participant devices, such as by using a group quality of service metric to select the devices, or extending the round execution parameters to include additional devices, may have an impact on DML performance.

A method of configuring a field device includes identifying an original Open Platform Communications Unified Architecture (OPC UA) server provided for a field device of the same type; creating a data set of values of parameters of the original OPC UA server; storing the created data set of the values of parameters of the original OPC UA server in a storage medium separate to the original OPC UA server; and generating a configuration for the field device comprising utilizing the created data set of the values of parameters of the original OPC UA server in the storage medium separate to the original OPC UA server.

Systems and methods for facilitating a multi-modal transportation service are provided. The method includes obtaining a request for an aerial transport from a user via user device and generating a multi-modal transportation itinerary for the user to facilitate the aerial transport of the user. The method includes determining a state change indicative of the progress of the user through the transportation service and adjusting an aerial software application running on an aerial device associated with an aerial service provider based on the state change. The method includes determining a subsequent state change occurring after the state change, determining a ground vehicle to provide a ground transportation for the user during another leg of the multi-modal transportation service based on the subsequent state, and adjusting a ground software application running on a ground device associated with the ground vehicle service provider based on the subsequent state change.

The present disclosure relates to an apparatus, a method, and a storage medium for federated learning (FL). Various embodiments for FL are described. In an embodiment, a central processing apparatus can be configured to, for a first one of a plurality of distributed computing apparatuses: receive a report message from the first distributed computing apparatus, the report message including at least one of training data set information or device information of the first distributed computing apparatus; evaluate FL performance of the first distributed computing apparatus based on the report message of the first distributed computing apparatus; determine wireless resource requirements of the first distributed computing apparatus based on the FL performance of the first distributed computing apparatus; and notify a wireless network, via a message, of configuring wireless resources for the first distributed computing apparatus based on the wireless resource requirements.

In some examples, migration context and flow graph based migration control may include ascertaining an application that is to be migrated from a physical environment to a cloud environment, and determining a migration issue associated with the migration of the application. Migration context and flow graph based migration control may further include identifying, from a historical issue database, a plurality of historical issues, determining, for the migration issue and the plurality of historical issues, unified proximities, sorting, based on the determined unified proximities, the historical issues, selecting, from the sorted historical issues, a topmost historical issue, and determining, from the topmost historical issue, a resolution associated with the topmost historical issue. Further, migration context and flow graph based migration control may include executing the resolution to resolve the migration issue, and performing, based on the resolved migration issue, migration of the application from the physical environment to the cloud environment.

An autonomous futures contract orchestration platform includes processors programmed with non-transitory computer-readable instructions to collectively execute receiving, from a data source, an indication associated with a product that relates to an entity that at least one of purchases or sells the product. The instructions include predicting a baseline cost of at least one of purchasing or selling the product at a future point in time based on the indication. The instructions include retrieving a futures cost, at a current point in time, of a futures contract for the product. The instructions include generating a risk threshold based on a specified risk tolerance of the entity indicating a difference between the baseline cost and the futures cost. The instructions include executing a smart contract for the futures contract based on the baseline cost, the futures cost, and the risk threshold.

Methods and apparatuses for logical time sensitive network (TSN) bridge are disclosed. According to an embodiment, a session management node receives, from a mobility management node in a mobile network, a first request for establishing a protocol data unit (PDU) session for a terminal device which is associated with a port of a logical TSN bridge. The session management node obtains a first port number of the logical TSN bridge at the side of the terminal device. The session management node obtains configuration information of the logical TSN bridge at a side of a user plane node corresponding to the PDU session

Disclosed is an integrated clustering system including a master node that sets environment setting for clustering and generate an access token by installing a management program, a plurality of worker nodes that set environment setting based on an environment variable including an IP address of the master node and the access token and perform clustering with the master node by installing the management program, and a system control unit that extracts runtimes of clustering groups including the master node and the plurality of worker nodes which are clustered, and compares the runtime of one of the clustering groups with the runtimes of other clustering group than the one clustering group.

According to one embodiment, a software update system for an Information Handling System (IHS) with hardware components including at least one directly managed hardware component and multiple proxy managed hardware components that are managed by one or more controller devices. The software update system has computer-readable instructions for, in response to receiving a request to perform a software update on the hardware components, partitioning the directly managed hardware component from the proxy managed hardware components, grouping the proxy managed hardware components according to each of the controller devices, and generating an Application Program Interface (API) call that specifies the group associated with each of the controller devices. The software update system then sends the API call to the directly managed hardware component, wherein the directly managed hardware component is configured to communicate with each of the controller devices for updating the proxy managed hardware components according to the API call.