A novel quality-of-service-aware web services composition using biogeography-based optimization algorithm

被引:40
|
作者
Sangaiah, Arun Kumar [1 ,2 ]
Bian, Gui-Bin [1 ]
Bozorgi, Seyed Mostafa [3 ]
Suraki, Mohsen Yaghoubi [4 ]
Hosseinabadi, Ali Asghar Rahmani [5 ]
Shareh, Morteza Babazadeh [6 ]
机构
[1] Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
[2] Vellore Inst Technol VIT, Sch Comp Sci & Engn, Vellore 632014, Tamil Nadu, India
[3] Islamic Azad Univ, Tehran North Branch, Dept Comp Engn, Tehran, Iran
[4] Islamic Azad Univ, Qazvin Branch, Dept IT & Comp Engn, Qazvin, Iran
[5] Islamic Azad Univ, Ayatollah Amoli Branch, Young Researchers & Elite Club, Amol, Iran
[6] Islamic Azad Univ, Babol Branch, Dept Comp Engn, Babol Sar, Iran
关键词
Web services composition; Web service; Quality of service; Biogeography-based optimization; Cloud computing; DIFFERENTIAL EVOLUTION; GENETIC ALGORITHM; PARTICLE SWARM; SELECTION; PARADIGM; ABC;
D O I
10.1007/s00500-019-04266-y
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
With the development of technology and computer systems, web services are used to develop business processes. Since a web service only performs a simple operation, web services composition has become important to respond to these business processes. In recent times, the number of existing web services has grown increasingly; therefore, similar services are presented increasingly. These similar web services are discriminated based on the various quality of service (QoS) parameters. These quality parameters include cost, execution time, availability, and reliability. In order to have the best QoS, each user should select a subset of services that presents best quality parameters. On the other hand, due to huge number of services, selecting web services for composition is an NP-hard optimization problem. This paper presents an efficient method for solving this problem using biogeography-based optimization (BBO). BBO is a very simple algorithm with few control parameters and effective exploit. The proposed method offers promising solutions to this problem. Evaluation and simulation results indicate efficiency and feasibility of the proposed algorithm.
引用
收藏
页码:8125 / 8137
页数:13
相关论文
共 50 条
  • [31] An innovative approach for QoS-aware web service composition using whale optimization algorithm
    Dahan, Fadl
    SCIENTIFIC REPORTS, 2024, 14 (01):
  • [32] Efficient and merged biogeography-based optimization algorithm for global optimization problems
    Zhang, Xinming
    Kang, Qiang
    Tu, Qiang
    Cheng, Jinfeng
    Wang, Xia
    SOFT COMPUTING, 2019, 23 (12) : 4483 - 4502
  • [33] Hybrid Algorithm Based on Biogeography-based Optimization and Differential Evolution for Global Optimization
    Ren Zi-wu
    Zhu Qiu-guo
    PROCEEDINGS OF THE 2014 9TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS (ICIEA), 2014, : 754 - +
  • [34] Optimization of software cost estimation model based on biogeography-based optimization algorithm
    Ullah, Aman
    Wang, Bin
    Sheng, Jinfang
    Long, Jun
    Asim, Muhammad
    Sun, Zejun
    INTELLIGENT DECISION TECHNOLOGIES-NETHERLANDS, 2020, 14 (04): : 441 - 448
  • [35] Independent Global Constraints-aware Web Service Composition Optimization Based on Genetic algorithm
    Liu Xiangwei
    Xu Zhicai
    Yang Li
    2009 INTERNATIONAL CONFERENCE ON INDUSTRIAL AND INFORMATION SYSTEMS, PROCEEDINGS, 2009, : 52 - +
  • [36] Construction biogeography-based optimization algorithm for solving classification problems
    Mohammed Alweshah
    Neural Computing and Applications, 2019, 31 : 5679 - 5688
  • [37] Power grid partition with improved biogeography-based optimization algorithm
    Liu, Fangyu
    Gu, Bruce
    Qin, Shuwen
    Zhang, Kaiyan
    Cui, Lei
    Xie, Gang
    SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS, 2021, 46
  • [38] A Novel Adaptive Web Service Selection Algorithm Based on Ant Colony Optimization for Dynamic Web Service Composition
    Wang, Denghui
    Huang, Hao
    Xie, Changsheng
    ALGORITHMS AND ARCHITECTURES FOR PARALLEL PROCESSING, ICA3PP 2014, PT I, 2014, 8630 : 391 - 399
  • [39] Set Covering Problem Resolution by Biogeography-Based Optimization Algorithm
    Crawford, Broderick
    Soto, Ricardo
    Riquelme, Luis
    Olguin, Eduardo
    Misra, Sanjay
    COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2016, PT I, 2016, 9786 : 153 - 165
  • [40] Construction biogeography-based optimization algorithm for solving classification problems
    Alweshah, Mohammed
    NEURAL COMPUTING & APPLICATIONS, 2019, 31 (10): : 5679 - 5688