Cloud data central task allocation method, device and system

Abstract

The invention discloses a cloud data central task allocation method, device and system and belongs to the field of cloud computing system control. The cloud data central task allocation method comprises the steps that firstly, operation state information of mainframes is collected, then current receivable task allowances of all mainframes are analyzed, a task allocation scheme is generated according to the receivable task allowances, and finally task allocation is performed according to flag variables. By means of the cloud data central task allocation method, device and system, the operation states of all mainframes in a data center are traced in real time, the performance change trend of the mainframes is prejudged, newly-arrived tasks are selectively allocated to the reasonable mainframes for execution so as to reduce task congestion occurrence rate and achieve load balance.

Description

technical field [0001] The invention belongs to the field of cloud computing system control, and in particular relates to a cloud data center task allocation method, device and system. Background technique [0002] Cloud computing is an Internet-based computing method in which shared hardware and software resources and information can be provided to computers and other devices on demand. Compared with traditional software and computing forms, cloud computing has significant advantages such as loose coupling, on-demand, cost control, resource virtualization, heterogeneous collaboration, etc., making it more suitable for today's e-commerce, flexible manufacturing, mobile Internet and other applications . [0003] A cloud data center refers to a distributed computing system composed of multiple heterogeneous hosts connected by a network to carry enterprise-level applications that provide online cloud services. In the cloud data center, centralized and unified management of a ...

AI Technical Summary

Problems solved by technology

This strategy has the following disadvantages: due to ignoring the changing trend of host load, resource occupancy, availability and reliability, the traditional scheduling strategy may allocate a large number of new tasks to the current task with a large margin but a sharp deterioration in the running state It is very easy for these hosts to form load hotspots after a period of time; at the same time, although some hosts currently have little task margin, they are in the process of rapidly improving their running status, and traditional scheduling and allocation strategies may ignore these Hosts that can actually undertake more tasks, resulting in idle waste of system computing resources

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