A genetic programming approach to distributed execution of data-intensive web service compositions
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- @InProceedings{conf/acsc/YuMZ16,
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author = "Yang Yu and Hui Ma and Mengjie Zhang",
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title = "A genetic programming approach to distributed
execution of data-intensive web service compositions",
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publisher = "ACM",
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year = "2016",
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booktitle = "Proceedings of the Australasian Computer Science Week
Multiconference, ACSW '16",
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address = "Canberra, Australia",
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pages = "29:1--29:9",
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keywords = "genetic algorithms, genetic programming, Distributed,
Data-Intensive, Service Composition",
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isbn13 = "978-1-4503-4042-7",
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bibdate = "2016-02-11",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/conf/acsc/acsw2016.html#YuMZ16",
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URL = "http://dl.acm.org/citation.cfm?id=2843043",
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DOI = "doi:10.1145/2843043.2843046",
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acmid = "2843046",
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size = "9 pages",
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abstract = "The executions of composite web services are typically
co-ordinated by a centralized workflow engine. As a
result, the centralized execution paradigm suffers from
inefficient communication and a single point of
failure. This is particularly problematic in the
context of data-intensive processes. To that end, more
distributed and flexible execution paradigms are
required. In this paper, we present a genetic
programming approach to partitioning a BPEL
data-intensive process into a set of sub-processes
which can be executed in a fully distributed manner.
Meanwhile, the approach takes into account the
communication latency and costs inside and across the
partitions. The experimental results show that our
proposed approach outperforms two existing methods for
complex data-intensive processes.",
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notes = "ACE/ACSC/AISC/APCMM/AUIC/AWC",
- }
Genetic Programming entries for
Yang Yu
Hui Ma
Mengjie Zhang
Citations