A user dependent Web service QoS collaborative prediction approach using neighborhood regularized matrix factorization

Chen, Zhen; Shen, Limin; You, Dianlong; Li, Feng

doi:10.1109/cscwd.2016.7566007

Cited by 6 publications

(8 citation statements)

References 9 publications

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“…Hence, in our example, the two intervals are [1,4] and [7,9]. We have price(s 1 ) ∈ [1,4] and price(s 2 ) ∈ [7,9]. The RIM normalization of the data renders: f(s 1 , price) = 1 − 4−2 4−1 = 0.33, which is greater than f(s 2 , price) = 1 − 9−7 9−7 = 0.…”

Section: Examplementioning

confidence: 92%

“…Let us consider a set of Web services characterized by the criterion price, which takes its values within [1,9]. Let us assume that the user defines value constraints in its request such that the criterion price must be within [4,7]. Let us consider two Web services s 1 and s 2 such that price(s 1 ) = 2 and price(s 2 ) = 9.…”

Section: Examplementioning

confidence: 99%

“…When using the approach RIM, the normalization of the data proceeds on two different intervals that denote the ranges of values that are outside the ideal interval of the required values, namely, [4,7]. Hence, in our example, the two intervals are [1,4] and [7,9]. We have price(s 1 ) ∈ [1,4] and price(s 2 ) ∈ [7,9].…”

Section: Examplementioning

confidence: 99%

“…Indeed, many services with similar functionalities can be considered in the user request response . To cope with this issue, QoS (Quality of Service) criteria describing the non‐functional characteristics of Web services are considered in addition to promote the best services …”

Section: Introductionmentioning

confidence: 99%

“…The service l is the best service when no value constraints are expressed. However, if we restrict the value range of throughput and availability to [1,3] and [4,6], respectively, then all the candidate services are driven out. By using RIM, we are able to determine the closest element to meet the considered value constraints.…”

mentioning

confidence: 99%

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How to deal with QoS value constraints in MCDM based Web service selection

Serrai

Abdelli

Mokdad

et al. 2018

Concurrency and Computation

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Summary The aim of the current research is to develop a more accurate Web service selection approach that can deal with value constraints on QoS criteria in the user request. The purpose is to be able to promote services even when all the value constraints are not satisfied and hence rank them according to their closeness to meet the latter. For this effect, we use MCDM (Multi Criteria Decision making) methods together with suitable normalization techniques at different stages of the process. First of all, we consider an extension of the AHP method to compute and normalize the weights associated with the QoS criteria considered in the Web service selection. Second, we introduce a more consistent normalization technique, called OMRI, to normalize data according to value constraints. Third, we propose to extend different ranking MCDM methods to the OMRI normalization so that it becomes possible for them to cope with value constraints. The considered methods are SAW, TOPSIS, VIKOR, and WPM. To compare the accuracy of the extended ranking methods, we use the Borda compromise solution together with different similarity ratios. To validate the solution, several experiments have been conducted on a real dataset as well as on an artificial one.

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