QoS-based Cloud Manufacturing Service Composition using Ant Colony Optimization Algorithm

被引:0
|
作者
Neshati, Elsoon [1 ]
Kazem, Ali Asghar Pourhaji [2 ]
机构
[1] Islamic Azad Univ, Tabriz Branch, Dept Mech Engn, Tabriz, Iran
[2] Islamic Azad Univ, Tabriz Branch, Dept Comp Engn, Tabriz, Iran
关键词
Cloud computing; cloud manufacturing; service composition; ant colony optimization;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Cloud manufacturing (CMfg) is a service-oriented platform that enables engineers to use the manufacturing capacity in the form of cloud-based services that aggregated in service pools on demand. In CMfg, the integration of manufacturing resources across different areas and industries is accomplished using cloud services. In recent years, the interest in cloud manufacturing service composition has grown, due to its importance in different manufacturing applications. When no single service is capable of satisfying the need for a manufacturing service requester, the service combination may be useful in order to fulfill the purpose of the manufacturing service requester. Therefore, the problem of how efficient and effective interconnection of cloud manufactring services has come to fetch many research fields. In this paper, a new algorithm is presented using an ant colony optimization for the problem of cloud manufacturing service composition considering the quality of service.
引用
收藏
页码:437 / 440
页数:4
相关论文
共 50 条
  • [1] A hybrid artificial bee colony algorithm for optimal selection of QoS-based cloud manufacturing service composition
    Jiajun Zhou
    Xifan Yao
    The International Journal of Advanced Manufacturing Technology, 2017, 88 : 3371 - 3387
  • [2] A hybrid artificial bee colony algorithm for optimal selection of QoS-based cloud manufacturing service composition
    Zhou, Jiajun
    Yao, Xifan
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2017, 88 (9-12): : 3371 - 3387
  • [3] A Novel Ant Colony Optimization Algorithm for Large Scale QoS-Based Service Selection Problem
    Zhang, Changsheng
    Yin, Hao
    Zhang, Bin
    DISCRETE DYNAMICS IN NATURE AND SOCIETY, 2013, 2013
  • [4] A chaos control optimal algorithm for QoS-based service composition selection in cloud manufacturing system
    Huang, Biqing
    Li, Chenghai
    Tao, Fei
    ENTERPRISE INFORMATION SYSTEMS, 2014, 8 (04) : 445 - 463
  • [5] Ant colony based optimization model for QoS-based task scheduling in cloud computing environment
    Sharma N.
    Sonal
    Garg P.
    Measurement: Sensors, 2022, 24
  • [7] A QoS-based service composition optimization method
    Wang, Xiaolong
    Zou, Peng
    Wang, Peng
    He, Jun
    Chen, Liang
    PROCEEDINGS OF THE 1ST INTERNATIONAL WORKSHOP ON CLOUD COMPUTING AND INFORMATION SECURITY (CCIS 2013), 2013, 52 : 1 - 5
  • [8] Cloud service composition using an inverted ant colony optimisation algorithm
    Asghari, Saied
    Navimipour, Nima Jafari
    INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION, 2019, 13 (04) : 257 - 268
  • [9] Optimization of Resource Service Composition in Cloud Manufacture Based on Improved Genetic and Ant Colony Algorithm
    Wang Zhengcheng
    ADVANCES IN INTELLIGENT SYSTEMS AND COMPUTING (ECC 2021), 2022, 268 : 183 - 198
  • [10] A dynamic ant-colony genetic algorithm for cloud service composition optimization
    Yefeng Yang
    Bo Yang
    Shilong Wang
    Feng Liu
    Yankai Wang
    Xiao Shu
    The International Journal of Advanced Manufacturing Technology, 2019, 102 : 355 - 368