Task scheduling and resource provisioning system and method

Abstract

A computing system is provided for providing task schedules, comprising an agent manager, a schedule information database configured to store resource and / or task information, at least one configurable agent, a scheduling unit, wherein the agent manager is configured to submit configuration instructions to the at least one configurable agent based on configuration information received by the agentmanager, wherein the at least one configurable agent is adapted to monitor resources used and / or tasks executed in the computing system depending on the configuration instructions and to store resource and / or task information derived from the monitored resources and / or tasks in the schedule information database, and wherein the scheduling unit is configured to generate and output a task schedulebased on the resource and / or task information stored in the schedule information database.

Description

technical field [0001] The present invention relates to the fields of task scheduling and resource distribution, in particular to a computing system and method for providing task scheduling. [0002] The invention further provides computing systems and methods for managing task scheduling and resource issuance. [0003] The systems and methods can be used independently or in combination with each other. Background technique [0004] Task scheduling and resource issuance are widely employed techniques among various fields within the field of computer science. A task schedule specifies a method of allocating computing tasks to resources processing the computing tasks. A computing task may be a basic computing unit such as a thread, process, or data flow to be computed by a processor. As opposed to resource provisioning, scheduling computing tasks may involve preparing local or distributed resources to provide services to users, for example, establishing a virtual machine (v...

AI Technical Summary

Problems solved by technology

[0011] Existing solutions cannot capture hardware configuration changes of nodes when collecting resource-related information

Current task schedulers also do not provide a way to monitor the running information of tasks or the workload of resources assigned to tasks at the granularity necessary to reschedule tasks or reallocate resources in order to optimize current or future task scheduling

[0012] Also, existing task schedulers are only able to take into account explicit task requirements for resources, e.g. required CPU power or amount of memory, when scheduling requests to generate task schedules should be processed

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