A genetic-based approach to web service composition in geo-distributed cloud environment

Wang, Dandan; Yang, Yang; Mi, Zhenqiang

doi:10.1016/j.compeleceng.2014.10.008

Cited by 91 publications

(55 citation statements)

References 15 publications

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“…Model [57], [36], [90], [62], [83], [169], [7], [99], [95], [21], [32], [204], [184], [150], [175], [23], [209], [156], [191], [9].…”

Section: Dimension Referencesmentioning

confidence: 99%

See 1 more Smart Citation

Designing service-based applications in the presence of non-functional properties: A mapping study

Neto

Vargas-Solar²,

Costa

et al. 2016

Information and Software Technology

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“…Model [57], [36], [90], [62], [83], [169], [7], [99], [95], [21], [32], [204], [184], [150], [175], [23], [209], [156], [191], [9].…”

Section: Dimension Referencesmentioning

confidence: 99%

“…SOC [198], [105], [47], [36], [131], [39], [145], [38], [197], [58], [142], [183], [91], [10], [4], [215], [120], [19], [21], [31], [45], [189], [212], [158], [1], [174], [164], [188], [191].…”

Section: Dimension Referencesunclassified

Designing service-based applications in the presence of non-functional properties: A mapping study

Neto

Vargas-Solar²,

Costa

et al. 2016

Information and Software Technology

View full text Add to dashboard Cite

“…According to [30], there are four basic models for a composite service executive path: sequence, parallel, selective, and circular. Through the aggregation of these basic models, the QoS value of any composite CMfg service can be obtained.…”

Section: Mathematical Modelmentioning

confidence: 99%

“…Currently, IA are widely used to solve such problems within a short time, including genetic algorithm (GA), particle swarm optimization (PSO), ant colony optimization (ACO), and the combination of the above algorithms and improved ones [27,30,32]. For CCSOS, the solution space is large, and the four QoS indexes are mutually dependent in complex composite service executive paths.…”

Section: Algorithm Designmentioning

confidence: 99%

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A hybrid artificial bee colony algorithm for optimal selection of QoS-based cloud manufacturing service composition

Zhou

Yao

2016

Int J Adv Manuf Technol

130

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With the advent of cloud manufacturing (CMfg), more and more services in CMfg platforms may provide the same functionality but differ in performance. In order to insure the manufacturing cloud to match the complicated task requirements, composited CMfg service optimal selection (CCSOS) is becoming increasingly important. This study proposes a new approach for such CCSOS problems, the so-called hybrid artificial bee colony (HABC) algorithm, which employs both the probabilistic model of Archimedean copula estimation of distribution algorithm (ACEDA) and the chaos operators of global best-guided artificial bee colony to generate the offspring individuals with consideration of quality of service (QoS) and CMfg environment. Different-scale CCSOS problems are adopted to evaluate the performance of the proposed HABC. Experimental results have shown that the HABC can find better solutions compared with such algorithms as genetic algorithm, particle swarm optimization, and basic artificial bee colony algorithm.

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Cloud service composition using minimal unsatisfiability and genetic algorithm

Wakrime

Rekik

Jabbour

2019

Concurrency and Computation

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SummaryThe software‐as‐a‐service layer of cloud computing has evolved much interest among the researchers in the academic and industry worlds. It is based on service‐oriented architectures and web service (WS) technology, which are used to offer a remotely accessible application. When a single WS is unable to satisfy all the customer's requirements, a WS composition (WSC) method is applied to connect together various available WSs for building distributed application, using discovery, compatibility checking, selection, and deployment steps. This paper has two‐fold contributions: The major one is the proposition of a new algorithm based on minimally unsatisfiable subset formal algorithm to compose WSs. This contribution ensures a faster WSC, which is prominent in an online context. The second contribution is the proposition of a new penalty‐based genetic algorithm to identify near‐optimal solutions whenever an exact one is not identified using our formal algorithm. Indeed, in some cases, many available WSs provide overlapping/identical functionality; in this context, the choice of participated services is given using quality of service. This work proposes a WSC ensuring to find out an exact or a near‐optimal solution according to the user need. A set of experimentations is applied to validate our contributions.

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A genetic-based approach to web service composition in geo-distributed cloud environment

Cited by 91 publications

References 15 publications

Designing service-based applications in the presence of non-functional properties: A mapping study

Designing service-based applications in the presence of non-functional properties: A mapping study

A hybrid artificial bee colony algorithm for optimal selection of QoS-based cloud manufacturing service composition

Cloud service composition using minimal unsatisfiability and genetic algorithm

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