Introducing Preferences over NFPs into Service Selection in SOA

Schröpfer, Christian; Binshtok, Maxim; Shimony, Solomon Eyal; Dayan, Aviram; Brafman, Ronen I.; Offermann, Philipp; Holschke, Oliver

doi:10.1007/978-3-540-93851-4_8

Cited by 14 publications

(9 citation statements)

References 10 publications

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“…In the last five years, many exiting works have focused on heterogeneous QoS preferences for atomic service selection, for example, QoS-Aware service selection [23], [41], qualitative preferences oriented service selection [47], and the combination of qualitative/quantitative preference for service selection [48].…”

Section: Related Work and Discussionmentioning

confidence: 99%

“…Pierre Châtel et al [49] proposed a LCP-net to model linguistic NFPs preference statements for service selection. Schröpfer et al [48] use UCP-net to model user preferences over the attribute values quantitatively, and they use TCP-net to assign relative importance and conditional relative importance between NFPs qualitatively.…”

Section: Related Work and Discussionmentioning

confidence: 99%

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Effective BigData-Space Service Selection over Trust and Heterogeneous QoS Preferences

Wang

et al. 2018

IEEE Trans. Serv. Comput.

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As the number of Cloud services is growing at a tremendous speed, there is an increasing number of service providers offering similar functionalities. Selecting services with user desired non-functional properties (NFPs) becomes of significant importance but triggers a number of Big Data related research issues. First, the selection decision should deal with a large volume of service NFPs data. Second, service selection needs to reflect diverse user preferences, including both qualitative and quantitative ones. Third, the uncertainty of the network and service load leads to high variability in NFPs. Fourth, as the trust values of service NFPs are collected via historic user's feedbacks, it brings the veracity dimension to the NFPs of services. Fifth, multiple and sometimes conflicting decision objectives for optimal service selection should be balanced. An effective service selection mechanism is in demand that can tackle all the above Big Data challenges in an integrated way to handle the highly diverse QoS with significant variability along with the trust related issues giving rise to data veracity. Existing investigations focus on either users' QoS preferences or their trust concerns but fail to provide a systematic solution to integrate both criteria in the selection process. In this paper, we tackle heterogeneous preferenceand trust-based service selection by developing a novel multi-objective optimization approach to make trade-off decision between service's trust value and user's QoS preference to rank candidate Cloud services based on their match degrees with users' requirements. We conduct extensive experiments to evaluate the effectiveness and efficiency of the proposed approach.

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Section: Related Work and Discussionmentioning

confidence: 99%

Section: Related Work and Discussionmentioning

confidence: 99%

Effective BigData-Space Service Selection over Trust and Heterogeneous QoS Preferences

Wang

et al. 2018

IEEE Trans. Serv. Comput.

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“…Schropfer et al [23] have recently proposed a TCP-net based formulation of qualitative user preferences over non-functional attributes for ranking and selecting individual services. In contrast, the focus of TCP-Compose is on the assembly of a set of composite services that constitute a non-dominated set with respect to a set of user-specified preferences and tradeoffs over non-functional attributes.…”

Section: Summary and Discussionmentioning

confidence: 99%

TCP − Compose ⋆ – A TCP-Net Based Algorithm for Efficient Composition of Web Services Using Qualitative Preferences

Santhanam

Basu

Honavar

2008

Service-Oriented Computing – ICSOC 2007

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Abstract. In many practical applications, trade-offs involving non-functional attributes e.g., availability, performance play an important role in selecting component services in assembling a feasible composition, i.e., a composite service that achieves the desired functionality. We present TCP-Compose , an algorithm for service composition that identifies, from a set of candidate solutions that achieve the desired functionality, a set of composite services that are non-dominated by any other candidate with respect to the user-specified qualitative preferences over non-functional attributes. We use TCP-net, a graphical modeling paradigm for representing and reasoning with qualitative preferences and importance. We propose a heuristic for estimating the preference ordering over the different choices at each stage in the composition to improve the efficiency of TCP-Compose . We establish the conditions under which TCP-Compose is guaranteed to generate a set of composite services that (a) achieve the desired functionality and (b) constitute a non-dominated set of solutions with respect to the user-specified preferences and tradeoffs over the nonfunctional attributes.

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“…In [3], an expressive and user-friendly preference model was proposed, which considers both qualitative and quantitative preferences, as well as atomic and composite preferences. In [10], qualitative preferences can be defined using the TCP network, which can handle the conditional preferences and relative importance of various non-functional properties, and quantitative preferences can be defined as utilities using the UCP network. Currently our paper only considers 2 types of user preferences and does not consider the relative importance of different properties.…”

Section: Related Workmentioning

confidence: 99%

Modeling User’s Non-functional Preferences for Personalized Service Ranking

Mirmotalebi

Chi

2012

Service-Oriented Computing

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Modeling users' online behavior has great benefit for many e-Commerce web sites and search engines. In the context of software service selection, if we could understand users' personal preferences, we could rank the services in a more satisfactory way. Many users have some general preferences on the desired values of non-functional properties (e.g. provider history, service popularity, etc.) of services, even if they may not explicitly define them. In this paper, we propose to build user profiles on these non-functional preferences, and then use them to personalize the ranking results for individual users. Our experiment showed that personalized ranking could promote the services matching with the user preferred non-functional values to higher positions, making it easier for users to identify their desired services. We also tested how different factors impact the degree of improvement on the ranking accuracy.

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Introducing Preferences over NFPs into Service Selection in SOA

Cited by 14 publications

References 10 publications

Effective BigData-Space Service Selection over Trust and Heterogeneous QoS Preferences

Effective BigData-Space Service Selection over Trust and Heterogeneous QoS Preferences

TCP − Compose ⋆ – A TCP-Net Based Algorithm for Efficient Composition of Web Services Using Qualitative Preferences

Modeling User’s Non-functional Preferences for Personalized Service Ranking

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