An apparatus and method for providing ML processing for one or more ML applications operating on one or more Internet of Things (IoT) devices includes receiving a ML request from an IoT device. The ML request can be generated by a ML application operating on the IoT device and include input data collected by the first ML application. A ML model to perform ML processing of the input data included in the ML request is identified and provided to an ML core for ML processing along with the input data included in the first ML request. The ML core produces ML processing output data based on ML processing by the ML core of input data included in the ML request using the ML model. The ML processing output data can be transmitted to the IoT device.

According to examples, an apparatus may include a memory on which is stored machine-readable instructions that may cause a processor to determine, for each of a plurality of members in a group, a respective least privilege level for a resource and determine, based on the determined respective least privilege levels, a privilege level to be assigned to the group for the resource. The instructions may also cause the processor to assign the determined privilege level to the group for the resource and apply the assigned privilege level to the members of the group for the resource.

The present disclosure describes a technique for honoring virtual machine placement constraints established on a first host implemented on a virtualized computing environment by receiving a request to migrate one or more virtual machines from the first host to a second host and without violating the virtual machine placement constraints, identifying an architecture of the first host, provisioning a second host with an architecture compatible with that of the first host, adding the second host to the cluster of hosts, and migrating the one or more virtual machines from the first host to the second host.

A method for managing data includes obtaining, by a first data node, a notification, wherein the first data node is associated with a first power zone group (PZG), and in response to the notification: selecting a second data node, wherein the second data node is not associated with the first PZG, sending a data processing request to the second data node, obtaining a response based on the data processing request, wherein the response specifies a confirmation by the second data node to service the data processing request, storing a ledger entry in a ledger service that indicates the confirmation, and initiating a data transfer based on the data processing request, wherein the first data node is associated with the PZG based on a primary power source of the first data node.

In another aspect, a system for machine learning using a distributed framework, includes a computing device communicatively connected to a plurality of remote devices, the computing device designed and configured to select at least a remote device of a plurality of remote devices, determine a confidence level of the at least a remote device, and assign at least a machine-learning task to the at least a remote device, wherein assigning further comprises assigning at least a secure data storage task to the at least a remote device and assigning at least a model-generation task to the at least a remote device.

An example operation may include one or more of receiving, by a risk score module, a blockchain transaction proposal, obtaining transaction proposal data, obtaining external data, computing a risk score from the transaction proposal data and the external data, comparing the risk score to a risk score threshold, providing an endorsement decision, based on the comparison, and one of endorsing or rejecting the transaction proposal.

Transaction-enabled systems and methods for royalty apportionment and stacking are disclosed. An example system may include a plurality of royalty generating elements (a royalty stack) each related to a corresponding one or more of a plurality of intellectual property (IP) assets (an aggregate stack of IP). The system may further include a royalty apportionment wrapper to interpret IP licensing terms and apportion royalties to a plurality of owning entities corresponding to the aggregate stack of IP in response to the IP licensing terms and a smart contract wrapper. The smart contract wrapper is configured to access a distributed ledger, interpret an IP description value and IP addition request, to add an IP asset to the aggregate stack of IP, and to adjust the royalty stack.

A non-transitory computer-readable storage medium storing a program that causes a computer to execute a process, the process includes acquiring first multiple tasks; dividing each task in the first multiple tasks in accordance with a cache size; classifying second multiple tasks in accordance with a range of data to be referred to at a time of execution of each task in the second multiple tasks that have been obtained by the dividing; and determining an execution order of tasks in a group for each group that has been obtained by the classifying.

An access control system controls access to a shared resource for various functional circuits. The access control system can include a comparison circuit, a processing circuit, and a selection circuit. The comparison circuit receives identification data associated with a functional circuit based on a transaction initiated by the functional circuit, and compares the identification data and reference data to generate a select signal. The processing circuit receives error data and response data outputted by the shared resource based on an execution of the transaction, and generates another response data. The selection circuit selects and outputs, based on the select signal, one of the response data outputted by the shared resource and the response data generated by the processing circuit as a transaction response that is to be provided to the functional circuit.

Embodiments of the invention may improve the performance of multi-processor systems in processing information received via a network. For example, some embodiments may enable configuration of a system such that information received via a network may be distributed among multiple processors for efficient processing. A user (e.g., system administrator) may select from among multiple configuration options, each configuration option being associated with a particular mode of processing information received via a network. By selecting a configuration option, the user may specify how information received via the network is processed to capitalize on the system's characteristics, such as by aligning processors on the system with certain NICs. As such, the processor(s) aligned with a NIC may perform networking-related tasks associated with information received by that NIC. If initial alignment causes one or more processors to become over-burdened, processing tasks may be dynamically re-distributed to other processors so as to achieve a more even distribution of the overall processing burden across the system.