scispace - formally typeset
Search or ask a question

How can skyline be used in web service selection? 


Best insight from top research papers

Skyline is used in web service selection to improve efficiency and satisfy user requirements. It is based on the concept of domination theory, where only services that are better than others in a set can survive. Skyline algorithms can be adapted to compute the regret constrained skyline, which relaxes hard constraints on Quality of Service (QoS) parameters and avoids returning empty results or missing interesting services . Clustering techniques can be applied to candidate web services based on QoS information to determine similar services, and the best performing clustering technique can be used for skyline-based selection . Skyline technology can be used to initially filter candidate services, and abstraction refinement technology can be used for service selection, resulting in significant performance advantages in terms of time . The Skyline technique is also used for web service selection of composite web services, considering QoS as a base criterion . The improved Skyline algorithm can effectively filter and reduce dominance checks among regions, improving execution efficiency .

Answers from top 5 papers

More filters
Papers (5)Insight
The paper proposes using a clustering-based approach to select web services. The best performing clustering technique is applied to candidate web services, and the most prominent set of web services is considered for skyline-based selection.
Proceedings ArticleDOI
Liang Xinmei, Qin Lu, Mingyu Li 
01 Dec 2019
6 Citations
The paper uses the Skyline algorithm for web service selection by comparing the QoS attributes of services and selecting the services with the best attributes.
Book ChapterDOI
Yamini Barge, Lalit Purohit, Soma Saha 
01 Jan 2021
5 Citations
The Skyline technique is used in web service selection by considering the Quality of Service (QoS) as a base criterion and selecting the most favorable services that dominate others in terms of performance.
Open accessProceedings ArticleDOI
Karim Benouaret, Sayda Elmi, Kian-Lee Tan 
01 Sep 2021
2 Citations
The paper discusses the use of skyline in QoS-based service selection, but does not provide specific details on how skyline can be used in web service selection.
Open accessProceedings ArticleDOI
Zhiyong Wu, Ke Meng, Xiukun Yan, Dayin Shi, Benjia Hu 
01 Sep 2021
3 Citations
Skyline technology is used in web service selection to initially filter many candidate services based on user needs.

Related Questions

Amazon web service5 answersAmazon Web Services (AWS) is a leading cloud computing service provider utilized by individuals, companies, and multinational businesses for its extensive offerings. AWS originated from Amazon's internal drive for efficiency monetization, evolving into a platform supporting various software products. Security is crucial in cloud applications, with symmetric security algorithms like Blowfish and RC6 recommended for confidentiality in AWS applications. To analyze the vast data in AWS, unconventional methods like Hadoop Map Reduce with Data Mining algorithms such as SVM and DT are employed for efficient big data analytics. Securing AWS operations at scale can be challenging, with issues like misconfigurations and data breaches prevalent, leading to the development of domain-specific modeling languages for AWS environments to assess security effectively.
What are the application of web sematic in big data?5 answersThe application of web semantics in big data is significant for enhancing data analysis processes and promoting interoperability. Semantic Web technologies can integrate data from various sources like web services, databases, and spreadsheets, addressing the challenges posed by data heterogeneity. By utilizing Linked Data as a data source, ontologies in data analysis, Semantic Web technologies for interoperability, and machine learning for data extraction, the Semantic Web can improve Big Data applications by providing a different paradigm for data analysis. Moreover, integrating ontology in big data ensures reliable interoperability, making data more meaningful and exploitable, while also hiding the heterogeneity of different data resources. This integration enhances big data management and analysis, ultimately benefiting decision-makers and users in various domains.
What factors should be considered when selecting a cloud provider for a specific project?5 answersWhen selecting a cloud provider for a specific project, several factors should be considered. These factors include the provider's performance, security measures, data management capabilities, personal data protection, and environmental-organizational aspects. Performance-related factors such as accessibility, response time, and capacity should be given priority. Security is also crucial, with reliability and governance being important considerations. Additionally, the costs associated with rental and network should be taken into account. It is important to conduct due diligence through research, training, and evaluation to select the right cloud provider for the organization. Collaboration with cloud managed service providers (MSPs) and cloud consultants is often necessary for monitoring and supporting the infrastructure and promoting the digital transformation agenda. The Cloud Security Alliance (CSA) provides a Consensus Assessment Questionnaire (CAIQ) that can be used to assess the security posture of cloud providers. Multi-criteria decision-making (MCDM) techniques can also be employed to rank cloud service providers based on user specifications.
How to use GIS for site selection?5 answersGIS can be used for site selection by following a systematic approach. First, gather the necessary spatial data about the area of interest, such as geology, provinces, buildings, and other relevant information. Next, apply criteria specific to the site selection problem, such as thermal conductivity, population density, energy consumption, or other relevant factors. This helps narrow down the potential sites. Geographic information systems can then be used to analyze and visualize the data, allowing for the identification of suitable locations. Additionally, the use of ontology-based multicriteria analysis methods can help address semantic heterogeneity and facilitate cooperation and collaboration among decision-makers in spatial group decision support systems. GIS can also be used in combination with analytic hierarchy process (AHP) to adjust the weights of criteria and determine the most suitable locations for large-scale photovoltaic (PV) plants. Finally, GIS and remote sensing techniques can be used for multi-criteria evaluation and weighted overlay analysis to determine suitable sites for various land-use zones, including solid waste disposal sites.
What are the common tricks to cheat Webometrics ranking?4 answersStep 1: Answer without citation Universities use various methods to manipulate Webometrics rankings, including creating web content through teachers and students, forming distributed learning communities, involving other organizations, and adding web addresses to bibliographic references. Additionally, some institutions face challenges such as bureaucratic barriers, connectivity issues, and inadequate knowledge on Webometrics, hindering their support for improved rankings. Step 2: Finding Citations - "Dubinskiy" - for creating web content through teachers and students, forming distributed learning communities, and involving other organizations. - "Kunosić" - for the challenges faced by institutions in supporting improved rankings. Step 3: Answer with citation Universities use various methods to manipulate Webometrics rankings, including creating web content through teachers and students, forming distributed learning communities, involving other organizations, and adding web addresses to bibliographic references ^[Dubinskiy]. Additionally, some institutions face challenges such as bureaucratic barriers, connectivity issues, and inadequate knowledge on Webometrics, hindering their support for improved rankings ^[Kunosić].
What ranking service fuzzy ahp can do?5 answersFuzzy AHP is a ranking service that can be used to rank various Cloud-Service providers (CSPs) based on parameters such as Reliability, Performance, Security, and Usability. It is also used for lean waste identification in industrial environments, where it helps prioritize the weights of different types of lean waste. Fuzzy AHP can be used in combination with other ranking techniques to overcome the shortcomings of objective and subjective approaches, resulting in better ranking results. In the context of construction projects, Fuzzy AHP is used to measure significant risks and evaluate them based on the project's objectives. Additionally, Fuzzy AHP is employed in tourism research to rank tourist facilities and determine development priorities based on social media data and reviews.