Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Multitask scheduling optimization method of knowledge service in cloud environment and scheduling system constructed via method

A technology of knowledge service and optimization method, applied in the direction of transmission system, digital transmission system, electrical components, etc., to achieve the effect of improving response efficiency

Inactive Publication Date: 2018-11-06
KUNMING UNIV OF SCI & TECH
View PDF9 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Aiming at the problems and deficiencies in the prior art above, the present invention provides a knowledge service multi-task scheduling optimization method in a cloud environment and a scheduling system constructed therefor to solve real-time problems existing in the knowledge service scheduling process in a cloud environment. Dynamic and execution time randomness issues, improve the response speed of the knowledge service process, and optimize the performance of the knowledge service system in the cloud environment

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Multitask scheduling optimization method of knowledge service in cloud environment and scheduling system constructed via method
  • Multitask scheduling optimization method of knowledge service in cloud environment and scheduling system constructed via method
  • Multitask scheduling optimization method of knowledge service in cloud environment and scheduling system constructed via method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0048] Embodiment 1: as figure 1 As shown, a knowledge service multi-task scheduling system in a cloud environment, the system includes:

[0049] The task scheduling buffer module is used to temporarily store some user task requests according to the service capability of the system when multiple users concurrently request, so as to ensure the balance between user tasks and platform resource service capabilities, and improve the response speed of the system to user requests;

[0050] The task analysis module is used to analyze the knowledge service task requirements submitted by users, degrade the vague and miscellaneous service tasks, and form multiple low-granularity knowledge service task sets that can be directly served by knowledge resources;

[0051] The knowledge resource scheduling module is used for preliminary knowledge resource matching work, matching and calculating the task characteristics requested by users with the static attributes of knowledge resources, and ob...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses a multitask scheduling optimization method of a knowledge service in the cloud environment and a scheduling system constructed via the method. According to the method, an optimization objective function and constraint conditions of multitask scheduling of the knowledge service in the cloud environment are determined, and an objective is optimized on the basis of a multi-group bidirectional driving cooperative search algorithm in the big data environment. A dynamic random function is introduced into knowledge service time of the optimized objective, the dynamic random characteristic of the service time in the practical operation process of the platform can be simulated effectively, the adaptation to the dynamic and random performances of the knowledge service processof the scheduling optimization algorithm is embodied, and the response efficiency of the knowledge service process is improved; and a mapping relation between a particle position vector and knowledgeresource distribution is established in a binary coding manner, the optimization algorithm is mapped into a discrete data space, a multi-group bidirectional driving mechanism is used to realize cooperative interactive searching between a common group and a model group, the algorithm is more adaptive to the random scheduling task, and the problem in optimization of multitask scheduling of the knowledge service is solved effectively.

Description

technical field [0001] The invention relates to a knowledge service multi-task scheduling optimization method in a cloud environment and a scheduling system constructed therefor, belonging to the field of knowledge services in a cloud environment. Background technique [0002] The group enterprise cloud service platform can provide users with manufacturing services throughout the product life cycle, and the knowledge resources flowing in all links of the product manufacturing life cycle activities are the core to support the operation of the cloud service system, which involves various cross-field Massive, distributed, multi-source and heterogeneous knowledge resources of multi-disciplinary and multi-specialty. Since the group enterprise cloud service platform is oriented to the collaborative manufacturing process of large-scale complex products, the cloud service set that enterprise users put forward knowledge service requirements to the platform involves collaborative simu...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): H04L29/08H04L12/24
CPCH04L41/5041H04L41/5051H04L41/5054H04L67/10H04L67/51H04L67/61H04L67/60H04L67/62H04L67/63
Inventor 阴艳超牛红伟徐凯吴仁杰张立童陈富钊
Owner KUNMING UNIV OF SCI & TECH
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com