A chaos control optimal algorithm for QoS-based service composition selection in cloud manufacturing system

Huang, Biqing; Li, Chenghai; Tao, Fei

doi:10.1080/17517575.2013.792396

Cited by 123 publications

(41 citation statements)

References 24 publications

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“…The searching process of traditional chaos optimization (CO) can be divided into two stages [23]: chaotic ergodic search and small perturbations. Chaotic ergodic search means huge mutations according to a group of chaotic sequential values.…”

Section: Experiments Results and Discussionmentioning

confidence: 99%

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A TQCS-based service selection and scheduling strategy in cloud manufacturing

Cao

Wang

Kang

et al. 2015

Int J Adv Manuf Technol

141

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Globalization, servitization, and customization in the marketplace are changing the way manufacturing enterprises do their business. Cloud manufacturing (CMfg) offers a possibility to perform large-scale manufacturing collaboration. However, CMfg systems are immature in many aspects. Service selection and scheduling is a key issue for practical implementation of CMfg. In this paper, a service selection and scheduling model is established, with criteria TQCS (time, quality, cost, and service) being considered. A fuzzy decision-making theory is adopted to transform TQCS values into relative superiority degrees. This is different from the traditional linear weighted method in most previous research, which results in large values of non-standardization error. The four relative superiority degrees are then combined linearly into an overall objective, in which the weight coefficients are calculated through analytic hierarchy process (AHP). Afterwards, ant colony optimization (ACO) is repurposed for the established service selection and scheduling model. Meanwhile, a selection mechanism is added to ACO (now ACOS) to enhance its validity. The simulation results demonstrate the practicality of the proposed model and the effectiveness of ACOS compared with other widely used algorithms.

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Section: Experiments Results and Discussionmentioning

confidence: 99%

“…An EMP is a PMU sequence, in which each PMU handles a counterpart LMT. [21] Resource service QoS modeling and evaluation in MGrid Tao et al [22] QoS based resource service optimal-selection in MGrid Huang et al [23] QoS based service composition optimal-selection in CMfg Energy…”

Section: Literature Reviewmentioning

confidence: 99%

A TQCS-based service selection and scheduling strategy in cloud manufacturing

Cao

Wang

Kang

et al. 2015

Int J Adv Manuf Technol

141

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“…Another classification was realized in Navimipour and Vakili . Cloud service composition approaches, in this work, are regrouped into frameworks‐based approaches, agents‐based approaches, and heuristics‐based approaches …”

Section: Background On Cloud Service Compositionmentioning

confidence: 99%

Multicloud service composition: A survey of current approaches and issues

Lahmar¹,

Mezni

2018

J Software Evolu Process

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During the last decade, cloud computing became a natural choice to host and provide various computing resources as on‐demand services. To better satisfy user requirements, cloud services may be combined while considering the constraints of the virtualized environment, including security policies, resources availability, and interoperability. Extensive surveys have been conducted to study the major issues related to the cloud service composition problem. However, very few works have studied such issues in a multicloud setting. To fill this gap, we provide in this paper a systematic literature review on multicloud service composition. We start with a background on service composition in single clouds. Then, we present the multicloud taxonomy, and we study how service composition was tackled by researchers in multicloud environments. Finally, we identify the challenges and the requirements of multicloud service composition, as well as the future directions.

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“…The chaos system has been mathematically proven to overcome the major drawbacks of classical random number systems. Due to the certainty, ergodicity, and stochastic property, recently, chaotic sequences have been adopted in evolutionary algorithms to avoid local optimization [25,[47][48][49][50][51]. With a chaos search strategy (CST), a population can perform across almost all states in a certain range without duplication.…”

Section: Chaos Searching Strategymentioning

confidence: 99%

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

Zhou

Yao

2016

Int J Adv Manuf Technol

125

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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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A chaos control optimal algorithm for QoS-based service composition selection in cloud manufacturing system

Cited by 123 publications

References 24 publications

A TQCS-based service selection and scheduling strategy in cloud manufacturing

A TQCS-based service selection and scheduling strategy in cloud manufacturing

Multicloud service composition: A survey of current approaches and issues

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

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