Discovery and Analysis About the Evolutionof Service Composition Patterns

Gao, Zhenfeng; Fan, Yushun; Li, Xiu; Gu, Liang; Wu, Cheng; Zhang, Jia

doi:10.13052/jwe1540-9589.1872

Cited by 9 publications

(2 citation statements)

References 28 publications

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“…The Resource-Aware Scheduling Algorithm (RASA) is particularly noteworthy, reducing makespan effectively in grid environments [19,20]. Similarly, the Reliable Scheduling Distributed in Cloud Computing (RIDC) algorithm has been developed to optimize processing time within cloud settings [21][22][23]. Furthermore, an Optimal Model for Priority-based Service Scheduling Policy has been proposed, targeting high Quality of Service (QoS) and throughput, showcasing the algorithm's aptitude for enhancing cloud computing services [24].…”

Section: Related Workmentioning

confidence: 99%

Intelligent Cloudlet Scheduling for Optimized Execution Time in Cloud Computing Environments

Yadav,

Varshney,

Kumar

2023

J. Comput. Mech. Manag

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Cloud computing has become a cornerstone of modern IT infrastructure, offering scalable and flexible resources. However, efficient resource management, particularly cloudlet scheduling, presents a significant challenge due to its NP-hard nature. This paper introduces a novel heuristic-based cloudlet scheduling algorithm aimed at minimizing execution time and improving load balancing in cloud computing environments. We detail the development and implementation of the algorithm, along with a simulation setup using the CloudSim toolkit to evaluate its performance against existing methods. Results from extensive simulations demonstrate that the proposed algorithm consistently reduces turnaround times, thus optimizing resource allocation. The findings suggest that our approach can significantly impact cloud computing efficiency, paving the way for improved service provider offerings and user satisfaction. The implications of these advancements are discussed, alongside potential directions for future research in dynamic cloud environments.

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Section: Related Workmentioning

confidence: 99%

Intelligent Cloudlet Scheduling for Optimized Execution Time in Cloud Computing Environments

Yadav,

Varshney,

Kumar

2023

J. Comput. Mech. Manag

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“…However, individual Web services may not be able to fully meet users' complex functional needs [8]. Therefore, Web service composition (i.e., mashup or workflow), especially customized service composition according to users' specific requirements, plays a key role in the field of Web services computing [9,17,31,36]. In order to make effective and efficient service composition for users, the first and paramount prerequisite is to mine user preferences.…”

Section: Introductionmentioning

confidence: 99%

Federated Latent Dirichlet Allocation for User Preference Mining

Wu,

Fan,

Zhang

et al. 2023

JWE

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In the field of Web services computing, a recent demand trend is to mine user preferences based on user requirements when creating Web service compositions, in order to meet comprehensive and ever evolving user needs. Machine learning methods such as the latent Dirichlet allocation (LDA) have been applied for user preference mining. However, training a high-quality LDA model typically requires large amounts of data. With the prevalence of government regulations and laws and the enhancement of people’s awareness of privacy protection, the traditional way of collecting user data on a central server is no longer applicable. Therefore, it is necessary to design a privacy-preserving method to train an LDA model without massive collecting or leaking data. In this paper, we present novel federated LDA techniques to learn user preferences in the Web service ecosystem. On the basis of a user-level distributed LDA algorithm, we establish two federated LDA models in charge of two-layer training scenarios: a centralized synchronous federated LDA (CSFed-LDA) for synchronous scenarios and a decentralized asynchronous federated LDA (DAFed-LDA) for asynchronous ones. In the former CSFed-LDA model, an importance-based partially homomorphic encryption (IPHE) technique is developed to protect privacy in an efficient manner. In the latter DAFed-LDA model, blockchain technology is incorporated and a multi-channel-based authority control scheme (MCACS) is designed to enhance data security. Extensive experiments over a real-world dataset ProgrammableWeb.com have demonstrated the model performance, security assurance and training speed of our approach.

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Crossover Service Pattern: Modeling and Computing

Chen

Yin

2023

Advanced Topics in Science and Technology in China

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Discovery and Analysis About the Evolutionof Service Composition Patterns

Cited by 9 publications

References 28 publications

Intelligent Cloudlet Scheduling for Optimized Execution Time in Cloud Computing Environments

Intelligent Cloudlet Scheduling for Optimized Execution Time in Cloud Computing Environments

Federated Latent Dirichlet Allocation for User Preference Mining

Crossover Service Pattern: Modeling and Computing

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