Cloud workflow scheduling method supporting any flow structure

Abstract

The invention mainly relates to a cloud workflow scheduling method supporting any flow structure, belongs to the field of information technologies and computers, and particularly relates to a cloud workflow scheduling algorithm which has universal applicability for various workflow models in a cloud computing environment and considers service quality indexes. According to the method, a task is modeled through a directed graph by taking a minimized cloud workflow execution expense as a scheduling target under a deadline constraint, so that simple and visual modeling advantages of a DAG graph are reserved and the method is suitable for workflow scheduling problems including logic structure selection and circulation; and static matching and dynamic adjustment of resources are subjected to task scheduling, so that the resource selection is optimized and very high universality is achieved.

Description

technical field [0001] The present invention mainly relates to a cloud workflow scheduling method that supports arbitrary process structures, and belongs to the field of information technology and computers. A Cloud Workflow Scheduling Algorithm for Quality of Service Indicators. Background technique [0002] With the development and maturity of computer Internet technology, cloud computing technology came into being. After nearly ten years of practice and exploration of cloud computing technology by major IT companies and related research institutions, cloud services have been accepted by more and more countries, enterprises, Personal favor and increasing demand have prompted many IT companies at home and abroad to launch their own cloud products. However, with the rapid development of cloud computing technology, the security, reliability and practicability of its products have attracted great attention from the supply and demand sides and scholars in related fields. Among...

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Problems solved by technology

[0003] Since the scheduling problem of cloud computing is an NP-hard (non-deterministic polynomial-hard) problem, this kind of problem can only seek an effective approximation algorithm and cannot be solved accurately. The current cloud workflow scheduling algorithm is mainly divided into best-effort based (best-effort based) workflow scheduling algorithm and workflow scheduling algorithm based on QoS constraint (QoSconstraint based) two categories, the former category of common algorithms are dynamic critical path algorithm DCP (Dynamic Critical Path) method, min- min method, HEFT (Heterogeneous Earliest FinishTime) method, etc. This type of scheduling algorithm only takes the minimum execution time as the scheduling goal, and is not suitable for commercial cloud workflow environments; the latter type of algorithm not only considers the workflow Execution time optimization, while considering the optimization of execution costs and non-functional indicators such as safety and reliability

Although there are many existing scheduling algorithms, most of them have certain limitations in practical application and do not have universal applicability to all workflow model structures, such as the work based on DAG (Directed Acyclic Gragh) graph Although the flow scheduling algorithm is simple and intuitive in expression, and has shown good performance in some practical applications, such an algorithm is not suitable for workflow scheduling problems with selection and loop logic control structures. The reason is It is a DAG diagram that cannot describe a workflow model with two logical structures of selection and circulation

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