OPTIMAL WEB SERVICE SELECTION AND COMPOSITION USING MULTI-OBJECTIVE BEES ALGORITHM

被引:17
|
作者
Kousalya, G. [1 ]
Palanikkumar, D. [2 ]
Piriyanka, P. R. [2 ]
机构
[1] SKCET, Dept Comp Sci & Engn, Coimbatore, Tamil Nadu, India
[2] Anna Univ Technol, Dept Comp Sci & Engn, Coimbatore, Tamil Nadu, India
关键词
D O I
10.1109/ISPAW.2011.40
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Web services have received much interest to support business-to-business or enterprise application integration but how to combine these services optimally in a continually growing search space is always a challenge. When there are a large number of Web services available, it is not easy to find an execution path of Web services composition that can satisfy the given request, since the search space for such a composition problem is in general exponentially increasing. In this paper, we design a Multi-objective Bees algorithm to solve this optimal service selection optimization problem. Bees algorithm helps to navigate through the whole search space. Web service data can be queried and a new subspace is built for each loop from which feasible solution can be calculated. Though global optimization cannot be guaranteed, an optimal solution can be obtained as a result.
引用
收藏
页码:193 / 196
页数:4
相关论文
共 50 条
  • [11] Multi-objective memetic approach for the optimal web services composition
    Azouz, Yacine
    Boughaci, Dalila
    EXPERT SYSTEMS, 2023, 40 (04)
  • [12] A Novel Multi-Objective Optimizing Web Services Selection Algorithm
    Fang, Qiqing
    Huang, Qingxian
    Liu, Gen
    Liu, Qinghua
    Deng, Bin
    INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND INDUSTRIAL AUTOMATION (ICITIA 2015), 2015, : 551 - 556
  • [13] A Hybrid Strategy Improved SPEA2 Algorithm for Multi-Objective Web Service Composition
    Wang, Hanting
    Du, Yugen
    Chen, Fan
    APPLIED SCIENCES-BASEL, 2024, 14 (10):
  • [14] MULTI-OBJECTIVE AND DISCRETE ELEPHANTS HERDING OPTIMIZATION ALGORITHM FOR QOS AWARE WEB SERVICE COMPOSITION
    Sadouki, Samia Chibani
    Tari, Abdelkamel
    RAIRO-OPERATIONS RESEARCH, 2019, 53 (02) : 445 - 459
  • [15] An adaptive robust service composition and optimal selection method for cloud manufacturing based on the enhanced multi-objective artificial hummingbird algorithm
    Zhang, Qianfu
    Li, Shaobo
    Pu, Ruiqiang
    Zhou, Peng
    Chen, Guanglin
    Li, Kaixin
    Lv, Dongchao
    Expert Systems with Applications, 2024, 244
  • [16] An adaptive robust service composition and optimal selection method for cloud manufacturing based on the enhanced multi-objective artificial hummingbird algorithm
    Zhang, Qianfu
    Li, Shaobo
    Pu, Ruiqiang
    Zhou, Peng
    Chen, Guanglin
    Li, Kaixin
    Lv, Dongchao
    EXPERT SYSTEMS WITH APPLICATIONS, 2024, 244
  • [17] Multi-Objective Service Composition Using Reinforcement Learning
    Moustafa, Ahmed
    Zhang, Minjie
    SERVICE-ORIENTED COMPUTING, ICSOC 2013, 2013, 8274 : 298 - 312
  • [18] Selection of Optimal Well Trajectory Using Multi-Objective Genetic Algorithm and TOPSIS Method
    Hossein Yavari
    Jafar Qajar
    Bernt Sigve Aadnoy
    Rasool Khosravanian
    Arabian Journal for Science and Engineering, 2023, 48 : 16831 - 16855
  • [19] Selection of Optimal Well Trajectory Using Multi-Objective Genetic Algorithm and TOPSIS Method
    Yavari, Hossein
    Qajar, Jafar
    Aadnoy, Bernt Sigve
    Khosravanian, Rasool
    ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2023, 48 (12) : 16831 - 16855
  • [20] A dynamic web service selection strategy with QoS global optimization based on multi-objective genetic algorithm
    Liu, SL
    Liu, YX
    Jing, N
    Tang, GF
    Tang, Y
    GRID AND COOPERATIVE COMPUTING - GCC 2005, PROCEEDINGS, 2005, 3795 : 84 - 89