Top-k Web Service Compositions Using Fuzzy Dominance Relationship

Benouaret, Karim; Benslimane, Djamal; Hadjali, Allel; Barhamgi, Mahmoud

doi:10.1109/scc.2011.86

Cited by 28 publications

(23 citation statements)

References 9 publications

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“…The advantages of this study are improvements on diversity of web services compositions while maintaining service composition with the highest score. The disadvantages of this method is limits in fuzzy method in composition of services to match the user requests through using set of comparative methods [7].…”

Section: Button-up Algorithmmentioning

confidence: 99%

Reducing the Calculations of Quality-Aware Web Services Composition Based on Parallel Skyline Service

Moradi¹,

Emadi²

2016

ijacsa

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Abstract-The perfect composition of atomic services to provide users with services through applying qualitative parameters is very important. As expected, web services with similar features lead to competition among the service providers. The key challenge to find an appropriate web service for composition occurs when multiple aspects of quality (such as response time, cost, etc.) are considered in the optimal composition of services. Skyline service provides the best service with consideration of qualitative parameters by using superior analysis. In this study, Skyline algorithm is used to find a set of best possible services compositions while taking into account qualitative parameters. The parallelism technique in this study, had significant impact on reducing response time and increasing the speed of service composition as well as reduction in composition calculations. The results of the analysis and evaluation of the proposed method shows optimum runtime and the best composition.

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Section: Button-up Algorithmmentioning

confidence: 99%

Reducing the Calculations of Quality-Aware Web Services Composition Based on Parallel Skyline Service

Moradi¹,

Emadi²

2016

ijacsa

View full text Add to dashboard Cite

show abstract

“…The system utilizes the history of users to amend the preferences of active users, thus improving the results of service selection. In our recent work [1,3], we propose an approach to automatically compose services, while taking into account the user preferences. User preferences are modeled using fuzzy sets.…”

Section: Preference-based Service Selectionmentioning

confidence: 99%

“…Thus, service selection is becoming important for helping users to identify desirable services. User preferences play a key role during the selection process [1][2][3]. However, in many practical situations, the responsibility to decide which is the appropriate service is shared among multiple parties, e.g., among the department heads of a university.…”

Section: Introductionmentioning

confidence: 99%

“…The users, in this case the department heads, have different preferences with respect to the service descriptions, as depicted in Table 1. User u 1 , has a budget of [7000, 10000] and expects to run simultaneously [5,10] processes; user u 2 cares much about data redundancy and expects a redundancy level of [3,5]; user u 3 expects to run simultaneously [8,12] processes requiring [80, 100] computing nodes.…”

Section: Introductionmentioning

confidence: 99%

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Majority-Rule-Based Web Service Selection

Benouaret

Sacharidis

Benslimane

et al. 2012

Web Information Systems Engineering - WISE 2012

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Abstract. Determining the appropriate service for a user request is a two step process. Initially, the available services whose description agrees with that of the request service are discovered. Then, the service selection process assists users in choosing the service that better matches their intention. In many practical situations, the responsibility to decide which is the appropriate service is shared among multiple parties, e.g., among the department heads of a university. The standard approach to such a service selection problem, is to discard services which are unanimously inappropriate, and return the rest. However, as the involved parties may have conflicting interests, it is possible that only few services are eliminated, and thus almost all discovered services need to be considered. This work addresses this shortcoming, by enforcing the majority rule: a service is discarded if the majority of the parties find it inappropriate. We formulate the majority-rule-based service selection problem based on the notions of dominance relationship and skyline. Furthermore, we propose an algorithm that (1) returns a more manageable set of services, eliminating many inappropriate ones, and (2) is more efficient that standard skyline techniques.

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“…Javadi et al [6] investigate cloud computing resource provision to extend the computing capacity of local clusters in the presence of failures and three steps in the resource provision including resource brokering, dispatch sequences and scheduling are considered. Benouaret et al [7] present an approach to automatically compose Data Web services while taking into account user preferences based on fuzzy sets and topk optimization. Liu et al [8] introduce a scheme to address the particularities of manufacturing resource service composition and optimization.…”

Section: Introductionmentioning

confidence: 99%

A QoS-satisfied Prediction Model for Cloud-service Composition Based on Hidden Markov Model

Wu¹,

Zhang²,

Zheng³

et al. 2013

Int. J. Onl. Eng.

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Abstract-There are various significant issues in cloud computing, such as service provision, service matching and service assessment, which have attracted researchers' attentions recently. QoS play an increasingly important role during the procedure of cloud-based service provision for seamless and dynamic integration of cloud-service components. In this paper, we focus on the QoS-satisfied prediction for cloud-service composited components and present a QoS-satisfied prediction model based on hidden Markov model. For a general process of cloud-service provision, if the user's QoS could not be satisfied only by one cloud-service component, the component composition should be considered to provide to user, where the QoSsatisfied capability of composited components need to be proactively predicted to guarantee the user's QoS. We discuss the proposed model in detail and proof the model partly. The simulation results show that our model can obtain rather high prediction accuracy rate.

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Top-k Web Service Compositions Using Fuzzy Dominance Relationship

Cited by 28 publications

References 9 publications

Reducing the Calculations of Quality-Aware Web Services Composition Based on Parallel Skyline Service

Reducing the Calculations of Quality-Aware Web Services Composition Based on Parallel Skyline Service

Majority-Rule-Based Web Service Selection

A QoS-satisfied Prediction Model for Cloud-service Composition Based on Hidden Markov Model

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