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
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