QoS-Based Web Services Selection

Wang, Hongbing; Tong, Ping; Thompson, Phil; Li, Yinsheng

doi:10.1109/icebe.2007.109

Cited by 5 publications

(5 citation statements)

References 16 publications

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“…Hence, the need arises to filter and select services based on their non-functional properties in addition to the functional attributes [ 49,60,64].…”

Section: Motivationmentioning

confidence: 99%

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Interactive QoS browsing for web service selection

Sambamoorthy¹

2022

Preprint

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In most of the current research works on Quality of Service (QoS) based web service selection, searching is usually the dominant way to find the desired services. This approach comes with the potential problem of framing search queries properly due to requestor's lack of knowledge or vague requirement about QoS attribute values. In this thesis, we propose an interactive QoS browsing mechanism that uses the concept of clustering to present the QoS value distribution to requestors followed by finer views of service quality. By analyzing various QoS attributes, we believe that the symbolic interval data is a proper type of representation, compared with the single valued numerical data. Therefore, we use interval data clustering algorithms to implement our browsing system. We conducted experiments on simulated QoS datasets to compare the performance of using different distance measures and show the effectiveness of the interval data clustering algorithm used. The result of the experiments show that the proposed approach provides an effective, user guided QoS based service selection approach that can conceivably overcome the problems with current approaches.

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“…Hence, the need arises to filter and select services based on their non-functional properties in addition to the functional attributes [ 49,60,64].…”

Section: Motivationmentioning

confidence: 99%

“…In this section, the defmitions of three popularly considered QoS attributes [35,55,64], used in this thesis work to analyze the proposed QoS based service selection method are presented. The three attributes are reliability, response time and price (or cost).…”

Section: Qos Attribute Definitionsmentioning

confidence: 99%

Interactive QoS browsing for web service selection

Sambamoorthy¹

2022

Preprint

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“…For the global optimization, Reference [15] proposes a global approach for Web services selection and optimization. During the process of composing web services, it is crucial to consider the services' QoS, Reference [16] proposes an approach to combine the same or similar functional services into classes of service which is convenient for selection. Reference [17] also presents a global QoS optimizing and multi-objective web services selection algorithm based on multi-objective ant colony optimization.…”

Section: Iirelated Workmentioning

confidence: 99%

“…Line 7 uses a function which is defined in Algorithm 3 to create a new vector. Line 8 computes the distance between input service's satisfaction and optimal with a function which employing formula (16) for calculation. After each service's distance has been calculated, we sort all the input service by their distance in line 10.…”

Section: Returnmentioning

confidence: 99%

A Mechanism for Web Service Selection and Recommendation Based on Multi-QoS Constraints

Chen

2010

2010 6th World Congress on Services

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Service-Oriented Architecture (SOA) provides a flexible framework for service composition. In a service market scenario, given a functional description of service, different providers may offer diverse service implementations that match such a functional description, but differ for some QoS attributes. It is increasingly vital to provide a service selection and recommendation mechanisms that best meet the QoS requirements of the service user. Different from most of the existing approaches to service selection, we consider a Web service selection and ranking mechanism with multi-QoS attributes, focusing on simulating degree of consumer satisfaction and hypothesizing consumer preference historical information. Efficient service selection mechanism and heuristic algorithm for consumer preference of multi-QoS are presented in this article and their performances are studied by simulations.

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“…U , C, B and D, have been specifically designed for this work as a secondary contribution, whilst 435 the rest were adopted from the literature (Zeng et al, 2004;Ardagna & Pernici, 2007;Canfora et al, 2005;Wang et al, 2007;Strunk, 2010). With the exception of T and L, all the properties have to be maximised.…”

mentioning

confidence: 99%

Evolutionary composition of QoS-aware web services: A many-objective perspective

Ramrez

Parejo

Romero

et al. 2017

Expert Systems with Applications

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Web service based applications often invoke services provided by thirdparties in their workflow. The Quality of Service (QoS) provided by the invoked supplier can be expressed in terms of the Service Level Agreement specifying the values contracted for particular aspects like cost or throughput, among others.In this scenario, intelligent systems can support the engineer to scrutinise the service market in order to select those candidates that best fit with the expected composition focusing on different QoS aspects. This search problem, a.k.a.QoS-aware web service composition, is characterised by the presence of many diverse QoS properties to be simultaneously optimised from a multi-objective perspective. Nevertheless, as the number of QoS properties considered during the design phase increases and a larger number of decision factors come into play, it becomes more difficult to find the most suitable candidate solutions, so more sophisticated techniques are required to explore and return diverse, competitive alternatives. With this aim, this paper explores the suitability of many-objective evolutionary algorithms for addressing the binding problem of web services on the basis of a real-world benchmark with 9 QoS properties. A complete comparative study demonstrates that these techniques, never before * Corresponding author. Tel.: +34 957 21 26 60Email addresses: aramirez@uco.es (Aurora Ramírez), japarejo@us.es (José Antonio Parejo), jrromero@uco.es (José Raúl Romero), sergiosegura@us.es (Sergio Segura), aruiz@us.es (Antonio Ruiz-Cortés) Preprint submitted to Expert Systems with ApplicationsOctober 31, 2016 applied to this problem, can achieve a better trade-off between all the QoS properties, or even promote specific QoS properties while keeping high values for the rest. In addition, this search process can be performed within a reasonable computational cost, enabling its adoption by intelligent and decision-support systems in the field of service oriented computation.

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QoS-Based Web Services Selection

Cited by 5 publications

References 16 publications

Interactive QoS browsing for web service selection

Interactive QoS browsing for web service selection

A Mechanism for Web Service Selection and Recommendation Based on Multi-QoS Constraints

Evolutionary composition of QoS-aware web services: A many-objective perspective

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