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

Wang, Chen; Ma, Hui; Chen, Gang; Hartmann, Sven; Branke, Jürgen

doi:10.1109/tetci.2020.3027870

Cited by 4 publications

(3 citation statements)

References 57 publications

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“…Recently, a novel privacy‐aware cloud service composition approach, called SFLA‐GA, has been proposed for optimizing the offered service compositions for enhancing the Quality of Service (QoS) in IoT environments 20 . Moreover, Chen et al 21 proposed a novel two‐stage GA‐based approach to offer a robust web service composition based on adaptive evolutionary control and efficient robustness measurement. However, it is important to note that genetic algorithms (GAs) are computationally intensive and may require a large amount of time and resources to Moreover, the two‐stage approach proposed by Chen et al may require extensive manual intervention in the second stage, which may be time‐consuming and may limit the scalability of the approach to larger and more complex service combinations.…”

Section: Related Workmentioning

confidence: 99%

An adaptive key selection method for the multilevel index model for effective service management in the cloud

Anjum

et al. 2023

Concurrency and Computation

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SUMMARYThe growing number of services processed and stored in the cloud has led to difficulties in managing and discovering the required services efficiently. Multilevel index model is an efficient method to manage and retrieve services in service repositories. When adding a new service to a multilevel index model, a key needs to be selected for the service, but existing key selection methods cannot adapt to the situation that hot services change over time. To address this problem, this article proposes an adaptive key selection method to improve the efficiency of service retrieval. However, the service addition operation of the adaptive key selection method is inefficient in the multilevel index model. For this reason, this article improves the multilevel index model by introducing local equivalence partition. This indexing model improves the service addition efficiency of the adaptive key selection method without affecting the service retrieval efficiency. It is experimentally demonstrated that the retrieval and addition efficiencies of the adaptive key selection method are close to the ideal state optimum under the multilevel index model with local equivalence partitioning.

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Section: Related Workmentioning

confidence: 99%

An adaptive key selection method for the multilevel index model for effective service management in the cloud

Anjum

et al. 2023

Concurrency and Computation

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“…In [121] Dong and Jiao present methods on how to achieve SLA level during Service Composition optimization. On the other hand, Wang et al in [128] show a method how to plan reactions to failures during execution.…”

Section: ) Related Algorithmsmentioning

confidence: 99%

Optimization of Business Process Execution in Services Architecture: A Systematic Literature Review

Górski

Woźniak

2021

IEEE Access

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Web services have become a standard way to provide functions of information systems. The number of web services grows rapidly with the increasing popularity of microservices architecture. In consequence, many business processes are executed entirely through web services. Therefore, optimizing the performance of business process execution may bring many benefits. There are many optimization methods in this area. Our systematic literature review aims to introduce available methods to researchers interested in the optimization of business process execution. We queried four databases: ACM, IEEE Xplore, Science Direct, and Springer. Out of 12150 initially found papers, we have selected 128 for the review. We have grouped methods presented in those papers into three stages of business process optimization: Resource Allocation, Service Composition, and Service Scheduling. Service Composition attracts the largest group of researchers with a vast majority of 119 articles in it. Moreover, the most popular are genetic algorithms. In general, researchers mainly propose heuristic methods that optimize business processes during run-time. We see the potential for further exploration at both Resource Allocation and Service Scheduling stages.

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“…On the other hand, factors such as the looseness, independence, and heterogeneity of the computing environment also bring new technical challenges to the guarantee of nonfunctional attributes such as real-time performance, security, reliability, and availability of service computing. In the open and dynamic network environment, the composite service-oriented computing model needs to implement a reliable software architecture with high reliability, adaptability, and self-management capability [3].…”

Section: Introductionmentioning

confidence: 99%

Trusted QoS Assurance Approach for Composite Service

Cai

Cui

et al. 2021

Security and Communication Networks

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The characteristics of service computing environment, such as service loose coupling, resource heterogeneity, and protocol independence, propose higher demand for the trustworthiness of service computing systems. Trust provisioning for composite services has become a hot research spot worldwide. In this paper, quality of service (QoS) planning techniques are introduced into service composition-oriented QoS provisioning architecture. By QoS planning, the overall QoS requirement of the composite service is decomposed into separate QoS requirement for every constituent atom service, the QoS level of which can subsequently be satisfied through well-designed service entity selection policies. For any single service entity, its QoS level is variable when the deployment environment or the load of service node changes. To mitigate the uncertainty, we put forward QoS preprocessing algorithms to estimate the future QoS levels of service entities with their history execution data. Then, based on the modeling of composite service and QoS planning, we design three algorithms, which include the time preference algorithm, cost/availability (C/A) preference algorithm, and Euclidean distance preference algorithm, to select suitable atomic services meeting the user’s requirements. Finally, by combining genetic algorithm and local-search algorithm, we propose memetic algorithm to meet the QoS requirements of composite service. The effectiveness of the proposed methods by which the QoS requirements can be satisfied up to 90% is verified through experiments.

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

Abstract: Please refer to published version for the most recent bibliographic citation information. If a published version is known of, the repository item page linked to above, will contain details on accessing it.

Cited by 4 publications

References 57 publications

An adaptive key selection method for the multilevel index model for effective service management in the cloud

An adaptive key selection method for the multilevel index model for effective service management in the cloud

Optimization of Business Process Execution in Services Architecture: A Systematic Literature Review

Trusted QoS Assurance Approach for Composite Service

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