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Search Space Reduction Approach for Self-adaptive Web Service Discovery in Dynamic Mobile Environment

  • Salisu GarbaEmail author
  • Radziah Mohamad
  • Nor Azizah Saadon
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1073)

Abstract

The proliferation of functionally similar Mobile Web Service (MWS) result in huge search space, the discovery of MWS on such large space increases the response time and probability of discovering irrelevant MWS irrespective of the matchmaking algorithm. The existing research on MWS discovery mostly focused on applying coarse-grained search space reduction that fails to deal with cold-start and data sparsity challenges at the expense of large computing resources. The proposed search space reduction is achieved by subsuming k-means in the modified negative selection algorithm (M-NSA) to place the service in an appropriate category so that the matching is only performed on the MWS in the target category. The experimental results show significant improvement in terms of accuracy of the categorization which can improve the MWS discovery in in a dynamic mobile environment (DME).

Keywords

Mobile Web Service Discovery Search space reduction Categorization algorithm 

Notes

Acknowledgements

We would like to thank the Ministry of Education (MOE) Malaysia for sponsoring the research through the Fundamental Research Grant Scheme (FRGS) with vote number 5F080 and Universiti Teknologi Malaysia for providing the facilities and supporting the research. In addition, we would like to extend our gratitude to the lab members in the EReTSEL Lab, School of Computing, Faculty of Engineering, Universiti Teknologi Malaysia for their invaluable ideas and support throughout this study.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Salisu Garba
    • 1
    Email author
  • Radziah Mohamad
    • 1
  • Nor Azizah Saadon
    • 1
  1. 1.School of Computing, Faculty of EngineeringUniversiti Teknologi Malaysia UTMSkudaiMalaysia

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