Service-Correlation Aware Service Selection for Composite Service Based on the Improved Dijkstra Algorithm

Ma, Sen; Wei, Chang; Xiaoxian, Cui

doi:10.1109/icee.2010.589

Cited by 3 publications

(2 citation statements)

References 5 publications

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“…Researchers also propose heuristic approaches to perform service composition in a reasonable time budget by sacrificing exact optimality to attain a near-optimal solution. Despite increasing interest in enforcement learning [24]- [28], heuristic search technics [29]- [34], A * algorithm [35], [36], hill-climbing [37] , BF algorithm [38] and Dijkstra [39], [40] were concurrent methods for heuristic-based service composition in current literature. In a graph, [41], or tree representation [42], heuristic search techniques are also applied to find the optimal path.…”

Section: A From None-heuristic To Metaheuristicmentioning

confidence: 99%

Hybrid Metaheuristics for QoS-Aware Service Composition: A Systematic Mapping Study

et al. 2022

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With the advent of Service-Oriented Architecture (SOA), services can be registered, invoked, and combined by their identical Quality of Services (QoS) attributes to create a new value-added application that fulfils user requirements. Efficient QoS-aware service composition has been a challenging task in cloud computing. This challenge becomes more formidable in emerging resource-constrained computing paradigms such as the Internet of Things and Fog. Service composition has regarded as a multi-objective combinatorial optimization problem that falls in the category of NP-hard. Historically, the proliferation of services added to problem complexity and navigated solutions from exact (none-heuristics) approaches to near-optimal heuristics and metaheuristics. Although metaheuristics have fulfilled some expectations, the quest for finding a high-quality, near-optimal solution has led researchers to devise hybrid methods. As a result, research on service composition shifts towards the hybridization of metaheuristics. Hybrid metaheuristics have been promising efforts to transcend the boundaries of metaheuristics by leveraging the strength of complementary methods to overcome base algorithm shortcomings. Despite the significance and frontier position of hybrid metaheuristics, to the best of our knowledge, there is no systematic research and survey in this field with a particular focus on strategies to hybridize traditional metaheuristics. This study's core contribution is to infer a framework for hybridization strategies by conducting a mapping study that analyses 71 papers between 2008 and 2020. Moreover, it provides a panoramic view of hybrid methods and their experiment setting in respect to the problem domain as the main outcome of this mapping study. Finally, research trends, directions and challenges are discussed to benefit future endeavours.

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Section: A From None-heuristic To Metaheuristicmentioning

confidence: 99%

Hybrid Metaheuristics for QoS-Aware Service Composition: A Systematic Mapping Study

et al. 2022

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“…None of the heuristics or exact methods approach, including linear programming techniques [25], [26], mixed integer programming [27], [28] and dynamic programming [29] asserted by a large body of evidence [30]- [33] to be efficient as long as service repositories are limited. However, heuristics methods [34]- [38], heuristic search technics [39]- [43], A * algorithm [44], [45], hill-climbing [45] , BF algorithm [46], and Dijkstra [47], [48] in current literature has encounter.…”

Section: Introductionmentioning

confidence: 99%

Hybrid Metaheuristics Using Rough Sets for QoS-Aware Service Composition

et al. 2022

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Quality of Service (QoS)-aware service composition plays an increasingly important role in various computational paradigms and delivery models, predominantly cloud computing. The proliferation of services with expanding quality attributes navigates this problem towards big service compositions, which fall under the umbrella of NP-hard. Within the realm of big services, performing composition also became a computationally expensive and challenging task. Since service composition is an NP-hard problem, numerous research aimed to determine optimal or near-optimal solutions within a reasonable budget. A large body of evidence suggests that metaheuristics could realize this goal to some extent. However, the proliferation of services with expanding quality attributes (search dimensions) may fail the most efficient techniques. In order to deal with the problem of big service composition, one trending approach has been devising hybrid metaheuristics methods by incorporating clustering techniques to minimize search space. This paper proposes a hybrid metaheuristic incorporated with a maximal discernibility heuristic based on rough set theory to perform composition in the subset of search space. Moreover, it introduces a parallel architecture and monitoring mechanism to provide immunity against premature convergence when the search space is minimized. The experiment was conducted for 25 datasets generated incrementally from a real-world QWS dataset, where the proposed hybrid solution effectively improves solution quality and reduces execution time with a statistical significance of 99 % confidence interval across diverse metaheuristics and datasets.

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Improved Vector Route Algorithm Bases on Raster Topological Space Model

Wang

2005

TENCON 2005 - 2005 IEEE Region 10 Conference

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Service-Correlation Aware Service Selection for Composite Service Based on the Improved Dijkstra Algorithm

Cited by 3 publications

References 5 publications

Hybrid Metaheuristics for QoS-Aware Service Composition: A Systematic Mapping Study

Hybrid Metaheuristics for QoS-Aware Service Composition: A Systematic Mapping Study

Hybrid Metaheuristics Using Rough Sets for QoS-Aware Service Composition

Improved Vector Route Algorithm Bases on Raster Topological Space Model

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