An Optimal Service-Selection Model Based on Capability and Quality of Resource Service

Author(s):  
Xiaodong Zhang ◽  
Zhan Dechen ◽  
Lanshun Nie ◽  
Tianqi Zhao ◽  
Xiao Xiong
2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Yan Wang ◽  
Jian-tao Zhou ◽  
Hong-yan Tan

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.


2012 ◽  
Vol 487 ◽  
pp. 357-364
Author(s):  
Xin Jun Li

In the paper, we propose an allocation scheme that minimizes the response time and cost of the solution subject to reliability and availability constraints in terms of expected value. The algorithm proposed in this paper aims to discover services with high QoS performance, and reduce the execute time at the same time. First, we identify the impact of various structural aspects of the composition in terms of the performance and outcomes of the composition. Then, an algorithm is proposed which can reduce the computing time and makes sure better quality of the services selection at the same time by examining a very tiny fraction of the solution space.Finally, we proves the advantage of the new algorithm by comparing the time obtained by our proposed algorithm with the one achieved by other algorithm.


2019 ◽  
Vol 10 (4) ◽  
pp. 334
Author(s):  
Bamei Tao ◽  
Quanwang Wu ◽  
Lei Guo ◽  
Junhao Wen ◽  
Yubiao Wang

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

2017 ◽  
Vol 7 (1.3) ◽  
pp. 146
Author(s):  
Rajeswari P ◽  
Jayashree K

The Cloud Computing uses high speed broadband for good Quality of Service (QoS) so that Cloud based application can be used with high speed which entails the minimum response time, less latency rate and reduced amount of loss of packets. Because of the ample range within the delivered Cloud solutions, from the customer’s aspect, it's emerged as irksome to decide whose providers they need to utilize and then what's the thought of his or her option. Bestowing suitable metrics is vital in assessing practices. QoS metrics are playing an important role in selecting Cloud providers and also revamping resource utilization efficiency. To guarantee a specialized product is published, describing metrics for assessing the QoS might be an essential requirement. To obtain high quality Cloud applications, Optimal Service Selection is needed. With the increasing number of Cloud services, QoS is usually selected for describing non-functional characteristics of Cloud services. In this paper, a widespread survey on QoS metrics for service vendors and QoS Ranking in Cloud Computing is presented.


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