scholarly journals A Cloud Service Selection Model Based on User-Specified Quality of Service Leve

2014 ◽  
Author(s):  
Chang-Ling Hsu
Keyword(s):  
Quality Of Service ◽  
Service Selection ◽  
Cloud Service ◽  
Selection Model ◽  
Model Based

scholarly journals CC-PSM: A Preference-Aware Selection Model for Cloud Service Based on Consumer Community

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Yan Wang ◽  
Jian-tao Zhou ◽  
Hong-yan Tan
Keyword(s):  
Clustering Algorithm ◽  
Service Selection ◽  
Cloud Service ◽  
Selection Model ◽  
Bipartite Network ◽  
Model Based ◽  
Selection Strategies ◽  
Hierarchical Clustering Algorithm ◽  
Full Consideration

In order to give full consideration to the consumer’s personal preference in cloud service selection strategies and improve the credibility of service prediction, a preference-aware cloud service selection model based on consumer community (CC-PSM) is presented in this work. The objective of CC-PSM is to select a service meeting a target consumer’s demands and preference. Firstly, the correlation between cloud consumers from a bipartite network for service selection is mined to compute the preference similarity between them. Secondly, an improved hierarchical clustering algorithm is designed to discover the consumer community with similar preferences so as to form the trusted groups for service recommendation. In the clustering process, a quantization function called community degree is given to evaluate the quality of community structure. Thirdly, a prediction model based on consumer community is built to predict a consumer’s evaluation on an unknown service. The experimental results show that CC-PSM can effectively partition the consumers based on their preferences and has good effectiveness in service selection applications.

PQsel: combining privacy with quality of service in cloud service selection

2016 ◽  
Vol 3 (3) ◽  
pp. 202 ◽  
Author(s):  
Li Lin ◽  
Tingting Liu ◽  
Jian Hu ◽  
Jian Ni
Keyword(s):  
Quality Of Service ◽  
Service Selection ◽  
Cloud Service

A dynamic cloud service selection model based on trust and SLA in cloud computing

2019 ◽  
Vol 10 (4) ◽  
pp. 334
Author(s):  
Bamei Tao ◽  
Quanwang Wu ◽  
Lei Guo ◽  
Junhao Wen ◽  
Yubiao Wang
Keyword(s):  
Cloud Computing ◽  
Service Selection ◽  
Cloud Service ◽  
Selection Model ◽  
Model Based

scholarly journals Trust-Enhanced Cloud Service Selection Model Based on QoS Analysis

PLoS ONE ◽  
2015 ◽  
Vol 10 (11) ◽  
pp. e0143448 ◽  
Author(s):  
Yuchen Pan ◽  
Shuai Ding ◽  
Wenjuan Fan ◽  
Jing Li ◽  
Shanlin Yang
Keyword(s):  
Service Selection ◽  
Cloud Service ◽  
Selection Model ◽  
Model Based

Multi-criteria Web Services Selection: Balancing the Quality of Design and Quality of Service

2022 ◽  
Vol 22 (1) ◽  
pp. 1-31
Author(s):  
Marwa Daaji ◽  
Ali Ouni ◽  
Mohamed Mohsen Gammoudi ◽  
Salah Bouktif ◽  
Mohamed Wiem Mkaouer
Keyword(s):  
Quality Of Service ◽  
Web Services ◽  
Web Service ◽  
State Of The Art ◽  
Service Selection ◽  
Service Design ◽  
Design Quality ◽  
Trade Off ◽  
Selection Approach

Web service composition allows developers to create applications via reusing available services that are interoperable to each other. The process of selecting relevant Web services for a composite service satisfying the developer requirements is commonly acknowledged to be hard and challenging, especially with the exponentially increasing number of available Web services on the Internet. The majority of existing approaches on Web Services Selection are merely based on the Quality of Service (QoS) as a basic criterion to guide the selection process. However, existing approaches tend to ignore the service design quality, which plays a crucial role in discovering, understanding, and reusing service functionalities. Indeed, poorly designed Web service interfaces result in service anti-patterns, which are symptoms of bad design and implementation practices. The existence of anti-pattern instances in Web service interfaces typically complicates their reuse in real-world service-based systems and may lead to several maintenance and evolution problems. To address this issue, we introduce a new approach based on the Multi-Objective and Optimization on the basis of Ratio Analysis method (MOORA) as a multi-criteria decision making (MCDM) method to select Web services based on a combination of their (1) QoS attributes and (2) QoS design. The proposed approach aims to help developers to maintain the soundness and quality of their service composite development processes. We conduct a quantitative and qualitative empirical study to evaluate our approach on a Quality of Web Service dataset. We compare our MOORA-based approach against four commonly used MCDM methods as well as a recent state-of-the-art Web service selection approach. The obtained results show that our approach outperforms state-of-the-art approaches by significantly improving the service selection quality of top- k selected services while providing the best trade-off between both service design quality and desired QoS values. Furthermore, we conducted a qualitative evaluation with developers. The obtained results provide evidence that our approach generates a good trade-off for what developers need regarding both QoS and quality of design. Our selection approach was evaluated as “relevant” from developers point of view, in improving the service selection task with an average score of 3.93, compared to an average of 2.62 for the traditional QoS-based approach.

Dynamic QoS-Aware Cloud Service Selection Using Best-Worst Method and Timeslot Weighted Satisfaction Scores

2020 ◽  
Author(s):  
Falak Nawaz ◽  
Naeem Khalid Janjua
Keyword(s):  
Decision Making ◽  
Service Selection ◽  
Cloud Service ◽  
Cloud Services ◽  
Satisfaction Score ◽  
Analytic Hierarchy ◽  
Hierarchy Process ◽  
Best Worst Method ◽  
Selection Of

Abstract The number of cloud services has dramatically increased over the past few years. Consequently, finding a service with the most suitable quality of service (QoS) criteria matching the user’s requirements is becoming a challenging task. Although various decision-making methods have been proposed to help users to find their required cloud services, some uncertainties such as dynamic QoS variations hamper the users from employing such methods. Additionally, the current approaches use either static or average QoS values for cloud service selection and do not consider dynamic QoS variations. In this paper, we overcome this drawback by developing a broker-based approach for cloud service selection. In this approach, we use recently monitored QoS values to find a timeslot weighted satisfaction score that represents how well a service satisfies the user’s QoS requirements. The timeslot weighted satisfaction score is then used in Best-Worst Method, which is a multi-criteria decision-making method, to rank the available cloud services. The proposed approach is validated using Amazon’s Elastic Compute Cloud (EC2) cloud services performance data. The results show that the proposed approach leads to the selection of more suitable cloud services and is also efficient in terms of performance compared to the existing analytic hierarchy process-based cloud service selection approaches.

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