The disclosed systems and methods are for scheduling web-resources for a malicious data comprising receiving requests to publish web-resources, and generating a graph structure comprising: a parent nodes associated with parent web-resources, a zero-vertex node being connected with the of parent nodes via zero-vertex edges, child nodes associated with child web-resources, and web-resource edges connecting the parent nodes, child nodes and sub-child nodes. Using the graph structure, assigning, to a given child node a first assigned trust score based on a lowest trust score of a subset of parent nodes connected to the given child node in the graph structure such that a web-resource edge length connecting the given, child node and the subset of parent nodes is a representative of the first assigned trust score, applying a shortest-path algorithm for calculating a shortest-path and based on the shortest-path determining at least one web-resource prioritized for the malicious data assessment.

The techniques described herein provide a system for executing a service that helps cloud resource providers manage unused cloud resources. Moreover, the service helps cloud resource consumers identify an optimal cloud platform to select for execution of an application. The service aggregates cloud resource information from multiple cloud providers and stores the cloud resource information in a data structure. The service then accesses the data structure to generate cloud resource offerings that can be published for review by different consumers. This process enables the consumers to see and compare cloud resource information, aggregated from multiple different cloud providers, in a single place (e.g., a complete and comprehensive user interface view into cloud resource information). More importantly, a consumer can make an efficient and informed decision as to which cloud provider and cloud platform to use for execution of an application.

A system for allocation of resources and processing jobs within a distributed system includes a processor and a memory coupled to the processor. The memory includes at least one process and at least one resource allocator. The process is adapted for processing jobs within a distributed system which receives jobs to be processed. The resource allocator is communicably coupled with at least one process, and is adapted to generate one or more sub-processes within a limit of one or more resources allocated to the process for processing jobs.

Deep reinforcement learning techniques are provided for resource allocation in a shared computing environment. An exemplary method comprises: obtaining a specification of a workflow of a plurality of concurrent workflows in a shared computing environment, wherein the specification comprises a plurality of workflow states and one or more control variables for the workflow in the shared computing environment; evaluating values of the control variables for an execution of the concurrent workflows using a reinforcement learning agent by (i) observing the states, including a current state, and (ii) obtaining an expected utility score for combinations of the control variables for the execution of the concurrent workflows given an allocation of resources of the shared computing environment corresponding to the combination of control variables in the current state; and providing an allocation of the resources of the shared computing environment reflecting the combination having the expected utility score that satisfies a predefined score criteria.

Methods, systems, and devices for providing computer implemented services using managed systems are disclosed. To provide the computer implemented services, the managed systems may be deployed to a location and operate in a predetermined manner conducive to, for example, execution of applications that provide the computer implemented services. When deployed to a location, the managed systems may be housed in a managed system frame. The managed system frames may include systems to guide placement of managed system in preferred frame units, remotely identify occupancy of the frame units, and/or the frame units against unexpected removals of or insertion of devices in the frame units.

A neural network system for predicting a polling time and a neural network model processing method using the neural network system are provided. The neural network system includes a first resource to generate a first calculation result obtained by performing at least one calculation operation corresponding to a first calculation processing graph and a task manager to calculate a first polling time taken for the first resource to perform the at least one calculation operation and to poll the first calculation result from the first resource based on the calculated first polling time.

A resource processing method includes: determining a current application scenario and usage data of the mobile terminal; inputting the usage data into a machine learning algorithm model corresponding to the current application scenario to obtain predicted recommendation parameters; and configuring resources of the mobile terminal based on the recommendation parameters.

A request is received to schedule a new software process. Description data associated with the new software process is retrieved. A workload resource prediction is requested and received for the new software process. A landscape directory is analyzed to determine a computing host in a managed landscape on which to load the new software process. The new software process is executed on the computing host.

Examples described herein relate to method and system for determining a response time for an action. A request for an action may be communicated from a source entity to a target entity. The action is generated by the source entity and which is to be responded by the target entity. Further, a response time corresponding to the action may be determined based on prior execution experience of one or more jobs associated with the action and a learning rate. Thereafter, the source entity may be allowed to wait for a response corresponding to a completion of the action from the target entity for at least a time duration corresponding to the response time.

Fault-tolerant and highly available configuration of distributed services including a computer-implemented method for role-based configuration discovery comprising receiving a request comprising an identifier of a role; identifying a first key, in a replica of a distributed configuration store, comprising a first value that matches the role identifier; identifying one or more other key-value pairs associated in the replica with the first key; and returning a response to an entity that sent the request comprising the value of at least one key-value pair that is specific to the role the service has. Also disclosed are techniques for log forwarding.