Integrated probability multi-search and solution acceptance rule-based artificial bee colony optimization scheme for web service composition

Arunachalam, N.; Amuthan, A.

doi:10.1007/s11047-019-09753-7

Cited by 17 publications

(11 citation statements)

References 16 publications

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“…This field has been widely studied in the past few years, focusing on developing effective and efficient EC techniques to find composite services with optimised QoS. To achieve such a goal, researchers have been working on developing new and effective representations of composite services for EC techniques, such as DAG-based [24,17,25,26], tree-based [4,7,27,28,29], tree-like based [7], and permutation-based representations [5,23,8]. The majority of these works also propose different representation-dependent genetic operators to explore large searching spaces, while some of them [8,17] propose new sampling techniques for breeding new promising solutions from the learned distributions (i.e., Node or Edge Histogram Matrix) of historical solutions.…”

Section: Literature On Web Service Composition Problemmentioning

confidence: 99%

Robustness Estimation and Optimisation for Semantic Web Service Composition With Stochastic Service Failures

Wang

Chen

et al. 2022

IEEE Trans. Emerg. Top. Comput. Intell.

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Section: Literature On Web Service Composition Problemmentioning

confidence: 99%

Robustness Estimation and Optimisation for Semantic Web Service Composition With Stochastic Service Failures

Wang

Chen

et al. 2022

IEEE Trans. Emerg. Top. Comput. Intell.

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“…This service management scheme is responsible for verifying and localizing the service change based on the limits of transaction and QoS constraints determined based on the user demands. This process of managing predominant service change need to consider the scope of the global or local composition, such that the proposed WSC-CSF-IABCO scheme [19], WSC-EABC-DSB-FL scheme [20] and WSC-IABCO-PMS-SAR schemes with local greedy method is enforced for facilitating effective dynamic web service composition. In addition, the classification of service is mainly used for process acceleration with the mechanism of service retrieval.…”

Section: V) Transaction and Qos Computing-based Adaptive Meta-heuristmentioning

confidence: 99%

Adaptive and Optimized Meta-Heuristic Framework for Establishing QoS and Transaction Properties-based Dynamic Web Service Composition

Arunachalam*¹

2019

IJRTE

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The dynamic web service composition based on QoS and transactional properties is considered to be the most important challenging research issues. Most of the works explored in the area of dynamic web service composition have mainly focused on some specific QoS parameters, which avoid potential factors from utilization. Further, the transaction properties also play a vital role in handling uncertainty which introduces most vital functionalities into the reactive environment. In this paper, an Adaptive and Optimized Meta-Heuristic Framework (AOMHF) is proposed for establishing dynamic web service composition based on QoS and transaction properties. This proposed AOMHF framework considered the user preferences and unpredictable service QoS for achieving reliable dynamic web service composition. This proposed AOMHF framework is developed as a dual staged web service composition scheme which incorporates the merits of monitoring mechanism which improves the possibility of improving and guaranteeing reliability and availability under reliable web service composition.

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“…Genetic algorithm [26,27,28,58,64,101,167,188,191,198] Particle swarm optimisation [7,76,82,112,127,196,194,207,199,231] Clonal selection algorithm [143,208] Ant colony optimisation [35,37,218] Articial bee Colony [11,206] Differential evolution algorithm [144] Cukoo search [24,36,66] Integer linear programming [62,63,67,216] Dynamic programming [77,204] Genetic Programming [42,117,126,152,182,202,221,222] Graph-based Genetic Programming [41,43] Genetic algorithm [44,…”

Section: Single-objectivementioning

confidence: 99%

“…Other EC methods have also been investigated to tackle web service composition problems. For example, Artificial Bee Colony (ABC) is an optimization technique that simulates the foraging behaviour of honey bees, and has been used for service selections in single-objective semiautomated web service composition [11,206]. For example, a recent work [11] proposes an Integrated Probability Multi-search and Solution Acceptance Rule-based Artificial Bee Colony Optimization Scheme, named IPM-SAR-ABCOS, to optimize transaction and QoS characteristics.…”

Section: Clonal Selection Algorithm (Csa) Is An Artificial Immune System (Ais) Techniquementioning

confidence: 99%

“…For example, Artificial Bee Colony (ABC) is an optimization technique that simulates the foraging behaviour of honey bees, and has been used for service selections in single-objective semiautomated web service composition [11,206]. For example, a recent work [11] proposes an Integrated Probability Multi-search and Solution Acceptance Rule-based Artificial Bee Colony Optimization Scheme, named IPM-SAR-ABCOS, to optimize transaction and QoS characteristics. The rule in IPM-SAR-ABCOS can enhance the rate of diversification and intensification in the employee bee phase and the onlooker bee respectively, preventing from being easily trapped into the local optimal.…”

Section: Clonal Selection Algorithm (Csa) Is An Artificial Immune System (Ais) Techniquementioning

confidence: 99%

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Comprehensive Quality-Aware Automated Semantic Web Service Composition

Wang

Chen

et al. 2017

AI 2017: Advances in Artificial Intelligence

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Automated web service composition is one of the ultimate goals of serviceoriented computing. It loosely couples web services to accommodate users' complex requirements. Evolutionary Computation (EC) techniques combined with AI planning have been successfully proposed to efficiently produce composite services with near-optimal Quality of Semantic Matchmaking (QoSM) and/or Quality of Service (QoS), which measure the satisfaction of the functional and non-functional requirements from users, respectively. Despite some recent progress, both the effectiveness and efficiency of existing approaches need further improvement to enhance the competitive advantage of service providers. The overall goal of this thesis is to propose novel EC-based fully automated service composition approaches that can effectively and efficiently solve challenging singleobjective, multi-objective, and dynamic service composition problems.Firstly, this thesis proposes two novel Estimation of Distribution Algorithm (EDA) based approaches (called EDA-NHM and EDA-EHM) and one memetic EDA-based approach with four different local search operators to single-objective fully automated web service composition that jointly optimizes QoSM and QoS. EDA-NHM and EDA-EHM are proposed with novel permutation-based and DAG-based representations to model the distribution of composition solutions with respect to varied service composition workflows. Two sampling techniques are also studied in EDA-NHM and EDA-EHM to effectively and efficiently sample new promising permutations and functionally valid DAGs, respectively. These two EDA-based approaches are compared to state-of-the-art works. The comparisons reveal that EDA-NHM produces better-quality composite services than EDA-EHM and the state-of-the-art works. On the other hand, EDA-EHM achieves the highest efficiency among all the competing EC-based methods, delivering moderate effectiveness. Furthermore, one proposed memetic approaches built upon EDA-NHM (called MEEDA-LOP) pushes the cutting-edge performance in terms of effectiveness and efficiency.Secondly, this thesis studies two categories of multi-objective service composition problems: one category aims to generate a set of approximated Pareto optimal solutions for users to choose from, while the other category aims to generate multiple composite services for multiple user segments with distinctive preferences on QoSM. To effectively and efficiently handle the first category of problems, a memetic approach based on Non-dominated Sorting Genetic Algorithm II (NSGA-II), called MNSGA2-EDA, is proposed by enhancing NSGA-II with EDA-based local search. The novelty of this method lies in the innovative use of EDA for effective and efficient local improvements, rather than for global exploration. MNSGA2-EDA is compared to state-of-the-art multi-objective works, for studying its performance. We found that MNSGA2-EDA achieves much higher effectiveness and efficiency in finding Pareto optimal solutions. The second category of problems can be naturally treated as multit...

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Integrated probability multi-search and solution acceptance rule-based artificial bee colony optimization scheme for web service composition

Cited by 17 publications

References 16 publications

Robustness Estimation and Optimisation for Semantic Web Service Composition With Stochastic Service Failures

Robustness Estimation and Optimisation for Semantic Web Service Composition With Stochastic Service Failures

Adaptive and Optimized Meta-Heuristic Framework for Establishing QoS and Transaction Properties-based Dynamic Web Service Composition

Comprehensive Quality-Aware Automated Semantic Web Service Composition

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