A Hybrid GP-Tabu Approach to QoS-Aware Data Intensive Web Service Composition
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Yu:2014:SEAL,
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author = "Yang Yu and Hui Ma and Mengjie Zhang",
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title = "A Hybrid GP-Tabu Approach to QoS-Aware Data Intensive
Web Service Composition",
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booktitle = "Proceedings 10th International Conference on Simulated
Evolution and Learning, SEAL 2014",
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year = "2014",
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editor = "Grant Dick and Will N. Browne and Peter Whigham and
Mengjie Zhang and Lam Thu Bui and Hisao Ishibuchi and
Yaochu Jin and Xiaodong Li and Yuhui Shi and
Pramod Singh and Kay Chen Tan and Ke Tang",
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volume = "8886",
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series = "Lecture Notes in Computer Science",
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pages = "106--118",
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address = "Dunedin, New Zealand",
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month = dec # " 15-18",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-3-319-13562-5",
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DOI = "doi:10.1007/978-3-319-13563-2_10",
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abstract = "Web service composition has become a promising
technique to build powerful business applications by
making use of distributed services with different
functions. Due to the explosion in the volume of data,
providing efficient approaches to composing data
intensive services will become more and more important
in the field of service-oriented computing. Meanwhile,
as numerous web services have been emerging to offer
identical or similar functionality, web service
composition is usually performed with end-to-end
Quality of Service (QoS) properties which are adopted
to describe the non-functional properties (e.g.,
response time, execution cost, reliability, etc.) of a
web service. In this paper, a hybrid approach that
integrates the use of genetic programming and tabu
search to QoS-aware data intensive service composition
is proposed. The performance of the proposed approach
is evaluated using the publicly available benchmark
datasets. A full set of experimental results show that
a significant improvement of our approach over that
obtained by the simple genetic programming method and
several traditional optimization methods, has been
achieved.",
- }
Genetic Programming entries for
Yang Yu
Hui Ma
Mengjie Zhang
Citations