Adaptive storage processing for storage-as-a-service, including detecting, by a cloud-based monitoring system, a storage system state for a storage system by monitoring the storage system in real-time remotely via a network; selecting, by the cloud-based monitoring system based on the storage system state, an entry in a tunables repository, wherein the entry in the tunables repository comprises a tunable parameter for the storage system state; accessing, by the cloud-based monitoring system via the network, a gateway for the storage system; and modifying, by the cloud-based monitoring system via the gateway, the tunable on the storage system based on the tunable parameter for the storage system state.

Optimizing a performance of a software function withing a content distribution network, such as a software-implemented virtual cable modem termination system (CMTS) network, a virtualized Radio Access Network (vRAN), a Passive Optical Network (PON), or a Wi-Fi network. The performance may be optimized by dynamically changing a deployment location within the content distribution network for the software function from an original location to an updated location using an instance management platform. The deployment location may be dynamically changing in response to a variety of trigger conditions or concerns, such as but not limited to a difference in compute resources, responding to latency needs or tolerances, and a desired cohabitation of data or other software.

Techniques for providing a framework for handling execution of HA flows in an active-active storage node configuration. The techniques include receiving notifications of functional statuses of processes and/or equipment associated with storage nodes in the active-active configuration, making determinations regarding how to address HA events occurring on the processes and/or equipment associated with the storage nodes based on the received notifications, and, in response to a request to execute an HA flow for a respective HA event, determining whether to refuse the request to execute the HA flow, service the request to execute the HA flow, abort one or more HA flows in execution, and/or postpone execution of the HA flow to a later time based on one or more dependencies defining conditions for the HA flow. In this way, mutual interference of HA flows or other process threads in the active-active configuration can be reduced or eliminated.

Adaptive storage processing for storage-as-a-service, including detecting, by a cloud-based monitoring system, a storage system state for a storage system by monitoring the storage system in real-time remotely via a network; selecting, by the cloud-based monitoring system based on the storage system state, an entry in a tunables repository, wherein the entry in the tunables repository comprises a tunable parameter for the storage system state; accessing, by the cloud-based monitoring system via the network, a gateway for the storage system; and modifying, by the cloud-based monitoring system via the gateway, the tunable on the storage system based on the tunable parameter for the storage system state.

A method to process data in a multicore SOC, includes receiving, from a MAC, input frames at a NIC of a RTOS implemented on a first core. The input frames are transmitted from the NIC to a frame processor of the RTOS for parsing and classifying in a first class related to RTOS tasks and a second class related to non RTOS tasks. The frames classified in the first class are transmitted to tasks of a sequencer of the RTOS and processed on the first core. The input frames classified in the second class are transmitted to a network device driver of a second OS implemented on a second core of the SOC, and processed on the second core. Output frames are transmitted to the frame processor, are classified and scheduled, and transmitted to the NIC and from the NIC to the MAC.

A system for hyper-dimensional computing for inference tasks may be provided. The device comprises an item memory for storing hyper-dimensional item vectors, a query transformation unit connected to the item memory, the query transformation unit being adapted for forming a hyper-dimensional query vector from a query input and hyper-dimensional base vectors stored in the item memory, and an associative memory adapted for storing a plurality of hyper-dimensional profile vectors and for determining a distance between the hyper-dimensional query vector and the plurality of hyper-dimensional profile vectors, wherein the item memory and the associative memory are adapted for in-memory computing using memristive devices.

An information processing apparatus includes a processor configured to perform connection to an external server that can be connected from the information processing apparatus and instruct the external server to execute processing as a first job, and then release a resource used in the first job, make an inquiry about whether or not the processing is completed to the external server, and wait for a response from the external server, in a case where a response indicating that the processing by the external server is completed is received in response to the inquiry, execute a second job that is different from the first job and is cooperated with the first job, and, in a case where a connection between the information processing apparatus and the external server is disconnected before or during the execution of the second job, make an inquiry about whether or not the processing is completed to the external server again and wait for a response from the external server.

An information handling system may include at least one processor; and a non-transitory memory coupled to the at least one processor. The information handling system may be configured to: receive a command associated with an Intelligent Platform Management Interface (IPMI) protocol; package the command for transmission according to a Redfish protocol; and transmit the packaged command to a Redfish interface of a management controller, wherein the management controller is configured to unpackage and execute the command.

A method and system for processing media content in Moving Picture Experts Group (MPEG) Network Based Media Processing (NBMP) includes receiving, from an NBMP source, a first message including a workflow descriptor document corresponding to a workflow for processing the media content; obtaining, based on the workflow, a task having a task template; obtaining, based on the task, a function having a function template; and managing the processing of the media content by transmitting, to a media processing entity, a second message instructing the media processing entity to perform the function based on the task. The first message, the workflow descriptor document, the task template, the function template, and/or the second message may be used to signal a scheme for processing the media content.

A fog service layer architecture is disclosed using hierarchical fog node deployment including the co-existence and interactions of the fog node with a cloud node. The architecture also includes a list of functions, capabilities or services that are hosted in each fog node. One or more fog management procedures may be run between fog nodes (or between fogs and the cloud) and may comprise a fog capability discovery procedure, a fog connection verification procedure, and a fog capability status report procedure. In addition, fog nodes may be configured to interact with each other to get particular services using one or more fog service procedures described herein.