Caching Hierarchical Skylines for Efficient Service Composition on Service Graphs

Alhosaini, Hadeel; Wang, Xianzhi; Yao, Lina; Chen, Yakun; Xu, Guandong

doi:10.1109/scc55611.2022.00015

Cited by 2 publications

(6 citation statements)

References 17 publications

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“…Thus, simulated datasets are usually generated for evaluation, which have been used in many studies [7]. However, to make the experimental results more solid, we utilized a public real-world dataset, named QWS [38], which is often used for the evaluation of traditional QoS-aware Web service compositions or recommendation approaches [27]. The dataset involves eight QoS properties on 2507 Web services.…”

Section: Methodsmentioning

confidence: 99%

“…They propose to group candidate services with the same subsidiary function into the same category so that the number of candidates can be further reduced after Skyline computation. Alhosaini et al [27] proposed a hierarchical Skyline-based approach to improve the efficiency of service composition by reusing varying levels of the Skyline service for the scenario that requests regarding the same or similar service as the subgraphs may occur frequently. Gavvala et al [28] proposed an QoS-aware cloud service composition approach by integrating the eagle strategy with the whale optimization algorithm to ensure the proper balance between exploration and exploitation.…”

Section: Related Workmentioning

confidence: 99%

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Scalable and Optimal QoS-Aware Manufacturing Service Composition via Business Process Decomposition

et al. 2023

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With the adoption of service-oriented manufacturing modes, more and more manufacturing services are released over manufacturing service platforms. As it is known, the problem of the QoS (Quality of Service)-aware manufacturing service composition is NP-hard. Thus, the optimization remains a challenging research issue, especially in the situation of large-scale manufacturing service data which arouse a scalability problem as well. To improve both the optimization performance and scalability of the QoS-aware manufacturing service composition, this paper proposes a scalable and optimal QoS-aware manufacturing service composition approach via business process decomposition. Specifically, the service composition process is decomposed by using a refined process structure tree (RPST). Moreover, an optimized service composition is achieved layer by layer based on the refined process structure tree in a bottom-up manner. For the atomic tasks or the compound tasks in the same layer of RPST, the corresponding QoS-aware service selection is optimized by calculating Skyline services, which can be carried out in parallel if necessary. When the optimization arrives at the root node, the complete service composition plans are derived. In our approach, the optimal manufacturing service candidates are picked out stage by stage. In this way, both the optimality and scalability of the whole approach can be guaranteed. Extensive experiments are conducted to verify the optimality and scalability of our approach.

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Section: Methodsmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Scalable and Optimal QoS-Aware Manufacturing Service Composition via Business Process Decomposition

et al. 2023

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“…Due to the uncertainty of QoS preferences, the diversity of recommendation results with respect to QoS should be incorporated. Based on these characteristics of QoS preferences, Zhang et al [23] put forward a diversified QoS-centered service recommendation algorithm. Given QoS constraints and candidate sets for users, all non-dominated services, namely Skyline services, are selected first.…”

Section: Related Workmentioning

confidence: 99%

“…By drawing from [23,24], Definition 1 defines the dominance relationship between two Web services. Based on Definition 1, the Skyline services can be defined as shown in Definition 2.…”

Section: Dynamic Skyline Servicesmentioning

confidence: 99%

“…In other words, the recommended services should include more representative services in as many QoS dimensions as possible. Based on the above observations, Zhang et al [23] propose a diversified QoS-centered service recommendation method. This approach uses the k-means clustering algorithm to divide Web services into k classes, and then a diversified service recommendation result is generated by selecting one service from each class.…”

Section: Introductionmentioning

confidence: 99%

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QoS-Centric Diversified Web Service Recommendation Based on Personalized Determinantal Point Process

Kang

Liang

et al. 2023

Electronics

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With the popularity and widespread adoption of the SOA (Service-Oriented Architecture), the number of Web services has increased exponentially. Users tend to use online services for their daily business and software development needs. With the large number of Web service candidates, recommending desirable Web services that meet users’ personalized QoS (Quality of Service) requirements becomes a challenging research issue, as the QoS preference is usually difficult to satisfy for users, i.e., the QoS preference is uncertain. To solve this problem, some recent works have aimed to recommend QoS-diversified services to enhance the probability of fulfilling the user’s latent QoS preferences. However, the existing QoS-diversified service recommendation methods recommend services with a uniform diversity degree for different users, while the personalized diversity preference requirements are not considered. To this end, this paper proposes to mine a user’s diversity preference from the their service invocation history and provides a Web service recommendation algorithm, named PDPP (Personalized Determinantal Point Process), through which a personalized service recommendation list with preferred diversity is generated for the user. Comprehensive experimental results show that the proposed approach can provide personalized and diversified Web services while ensuring the overall accuracy of the recommendation results.

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Caching Hierarchical Skylines for Efficient Service Composition on Service Graphs

Cited by 2 publications

References 17 publications

Scalable and Optimal QoS-Aware Manufacturing Service Composition via Business Process Decomposition

Scalable and Optimal QoS-Aware Manufacturing Service Composition via Business Process Decomposition

QoS-Centric Diversified Web Service Recommendation Based on Personalized Determinantal Point Process

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