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

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Abstract

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.

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Acknowledgements

We sincerely acknowledge that this work has been supported in part by the Chinese Academy of Sciences (CAS) President’s International Fellowship Initiative (PIFI) for Visiting Scientists via Grant No.: 2019VTB0005 and Youth Innovation Promotion Association of the Chinese Academy of Sciences under Grant 2018165. The authors are grateful for this support.

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Authors and Affiliations

  1. State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, 100190, China

    Arun Kumar Sangaiah & Gui-Bin Bian

  2. School of Computing Science and Engineering, Vellore Institute of Technology (VIT), Vellore, 632014, India

    Arun Kumar Sangaiah

  3. Department of Computer Engineering, Tehran North Branch, Islamic Azad University, Tehran, Iran

    Seyed Mostafa Bozorgi

  4. Department of IT and Computer Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran

    Mohsen Yaghoubi Suraki

  5. Young Researchers and Elite Club, Ayatollah Amoli Branch, Islamic Azad University, Amol, Iran

    Ali Asghar Rahmani Hosseinabadi

  6. Department of Computer Engineering, Babol Branch, Islamic Azad University, Babol, Iran

    Morteza Babazadeh Shareh

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  1. Arun Kumar Sangaiah
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  4. Mohsen Yaghoubi Suraki
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  5. Ali Asghar Rahmani Hosseinabadi
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Correspondence to Gui-Bin Bian.

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Communicated by Mu-Yen Chen.

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Sangaiah, A.K., Bian, GB., Bozorgi, S.M. et al. A novel quality-of-service-aware web services composition using biogeography-based optimization algorithm. Soft Comput 24, 8125–8137 (2020). https://doi.org/10.1007/s00500-019-04266-y

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