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A genetic algorithm based technique for QoS-aware Web service composition

Authors: Yilmaz, Ahmet Erdinç;

A genetic algorithm based technique for QoS-aware Web service composition

Abstract

Günümüzde en hızlı gelişen teknolojilerden biri de Web Servisi teknolojileridir. Web servisler XML tabanlı standartlarla tanımlanması sayesinde, platform bağımlılık sorununu çözerek diğer web servisleri kullanarak yeni servisler uyarlamaya uygundur. Bu uyarlama, eski servislerin tekrar kullanılması ile kaynakların daha az tüketilmesini sağlamaktadır. Web servis alanındaki ana unsurlar servislerin nasıl bağlanacağını belirleyen birleşik servis planın tanımlanması ve oluşturulan birleşik servisin toplam servis kalitesi puanını olabildiğince arttırmaktır. Servis kalitesini belirleyen bileşenler arasında servis ücreti, çalışma zamanı, bulunabilirlik, başarılı sonuç verme, güvenilirlik ve verimlilik en popüler olanlarıdır. Optimal birleşik servis planını bulmak NP-Zor problem olması sebebi ile optimizasyon tekniklerinin kullanılması çok popülerdir. Bu tezde, birleşik web servisi oluştururken kalite servis puanını optimize etmeyi amaçlayan yeni bir geliştirilmiş genetik algoritma sunulmaktadır.

Web Service technology is one of the most rapidly developing technologies. Since Web Services are defined by several XML-based standards to overcome platform dependency, they are very eligible to integrate with each other in order to establish new services. This composition enables us to reuse existing services, which results in less cost and time consumption. Currently the main issues with Web Service Composition is to define workflow of the services and maximizing the overall Quality of Service (QoS) of the composed service. Most common elements of QoS are execution cost, execution time, availability, successful execution rate, reliability and throughput. Since the selection of the optimal execution plan that maximizes the composition's overall QoS is NP-hard problem, applying optimization techniques is very popular. In this thesis, we propose an improved Genetic Algorithm to optimize the overall QoS of the composed service.

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Keywords

Computer Engineering and Computer Science and Control, Bilgisayar Mühendisliği Bilimleri-Bilgisayar ve Kontrol

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average