Web Service Selection Algorithm Research Articles

An Intelligent Bat Algorithm for Web Service Selection with QoS Uncertainty

Currently, the selection of web services with an uncertain quality of service (QoS) is gaining much attention in the service-oriented computing paradigm (SOC). In fact, searching for a service composition that fulfills a complex user’s request is known to be NP-complete. The search time is mainly dependent on the number of requested tasks, the size of the available services, and the size of the QoS realizations (i.e., sample size). To handle this problem, we propose a two-stage approach that reduces the search space using heuristics for ranking the task services and a bat algorithm metaheuristic for selecting the final near-optimal compositions. The fitness used by the metaheuristic aims to fulfil all the global constraints of the user. The experimental study showed that the ranking heuristics, termed “fuzzy Pareto dominance” and “Zero-order stochastic dominance”, are highly effective compared to the other heuristics and most of the existing state-of-the-art methods.

Service Discovery and Selection Based on Dynamic QoS in the Internet of Things

Web services are self-describing and self-contained modular applications based on the network. With the deepening of web service applications, service consumers have gradually increased their requirements for service functions and service quality. Aiming at how to select the optimal plan from a large number of execution plans with the same function and different QoS characteristics, this paper proposes a web service selection algorithm that supports QoS global optimization and dynamic replanning. The algorithm uses position matrix coding to represent all execution paths and replanning information of the service combination. By calculating the Hamming distance of the service quality between individuals, the quality of the service portfolio is improved. By specifying the total user time limit and implementing a good solution retention strategy, the problem of the impact of algorithm running time on service quality is solved. The experimental results show that the method proposed in this paper is effectively integrated into the development trend of QoS and close to the requester’s needs and can better meet user needs. This algorithm improves the user’s satisfaction with the returned service to a certain extent and improves the efficiency of service invocation.

GPU Accelerated TOPSIS Algorithm for QoS Aware Web Service Selection

Web service selection is the method of selecting the best web service based on non-functional aspects. With proliferation of web services, there is a demand for efficient approaches to select the best web services from the available pool. A number of Multi criteria decision making approaches are adopted for QoS aware web service selection. The exploitation in web service deployment increases the computation power in executing web service selection. Graphics processing unit (GPU) can achieve reduction in computation power by performing multiple tasks at a time. The independent tasks in the algorithm are parallelized by utilizing GPU in order to achieve more efficiency. This works proves that GPU acceleration can be utilized in parallelizing TOPSIS algorithm for web service selection.

A Comprehensive Web Service Selection Algorithm on Just-in-Time Scheduling

This paper proposes a comprehensive service selection algorithm (CSA) for improving performance and real-time arrangement in service selection. The algorithm integrates the service provider’s elicited preference and requestor’s planned time. This innovative CSA autonomously aggregates multiple requestors’ preferences over multicriteria from multiple providers, selecting the most suitable service provider on the basis of voting. The sequencing portion of the algorithm also runs based on time scheduling, where the extra cost of the system is minimal due to its small time window. The service arrangement process functions by identifying and utilizing the best solution for the 0-1 knapsack problem; the improved genetic algorithm finds solutions via coding and evolution. Experiment results show that the proposed CSA effectively simplifies the preference convergence of service requestors and optimizes the time scheduling of the service provider. The algorithm also enhances selection efficiency and reduces selection time, and it can be applied feasibly to multi-provider and multi-requestor service selection.

Optimized Weight Vector for QoS Aware Web Service Selection Algorithm Using Particle Swarm Optimization

Optimized Weight Vector for QoS Aware Web Service Selection Algorithm Using Particle Swarm Optimization

Research on the Improvement of Traditional Linear Weighted Algorithm for QoS-based Web Service Selection

At present, quality of service (QoS) has become an important guidance in selecting a satisfactory web service when many similar web services provide overlapping or identical functionalities. Therefore people have carried out many studies on definition and standardization of QoS properties and QoS-based selecting algorithms of web service. Current web service selection usually adopt linear weighted algorithm. But it still has some limitations. This paper proposes a new QoS-based algorithm developed from traditional linear weighted algorithm for web service selection. The main improvements include removing distinction of QoS properties value tendency, selecting fixed value and a hybrid subjective-objective approach to set the weight of each QoS property. We also present the analysis of the time complexity. Finally we do a comparison experiment between our algorithm and traditional algorithm. The results show that the improvements are feasible and our algorithm has better performance.

An Efficient Discrete Invasive Weed Optimization Algorithm for Web Services Selection

Efficient algorithm is required to select component services with end-to-end QoS constraints in dynamic composition of Web Services while optimizing the QoS of the composite service. In this paper, the services selection probelm is modeled as a nonlinear optimization with constraints, then a novel discrete invasive weed optimization web services selection algorithm is proposed. The proposed solution consists of two steps:first, a set of randomly generated feasible solutions are transformed into decimal code. Second, We utilize Gaussian diffusion to guide the population to spread in the solution space. The mutation probability and mutation step size of individual is dynamically adjusted by changing the stantard deviation of Gaussian distribution. Accordingly, the population diversity is ensured in the early stage to expand the search space, while the local search nearby excellent individuals is focused in the latter stage to ensure the global convergence. Theoretical analysis and experiment results indicate the efficiency, robustness and feasibility of our approach.

QoS-Aware Multiobjective Optimization Algorithm for Web Services Selection with Deadline and Budget Constraints

The problem of QoS-aware multiobjective optimization is an important issue for Web services selection in distributed computing environment. In this paper, a novel algorithm called MOASS (multiobjective optimization algorithm for web service selection) is proposed through analyzing the genetic operators such as constraint handling, the initial population generation, fitness assignment, and diversity preservation. Compared with MOEAWP (Yu et al., 2007), simulation results show that the feasible objective region can be filled uniformly with the optimal solutions obtained by MOASS under different test applications. In the case of higher constraints especially, MOASS can obtain more high-quality and evenly distributed nondominated solutions than MOEAWP.

Web Services Selection Algorithm Based on the Quality of Service

Web Services Selection Algorithm Based on the Quality of Service

Research on Transaction Web Service Selection Algorithm in WSC

Research on Transaction Web Service Selection Algorithm in WSC

Web service selection algorithm based on principal component analysis

Existing Web service selection approaches usually assume that preferences of users have been provided in a quantitative form by users. However, due to the subjectivity and vagueness of preferences, it may be impractical for users to specify quantitative and exact preferences. Moreover, due to that Quality of Service (QoS) attributes are often interrelated, existing Web service selection approaches which employ weighted summation of QoS attribute values to compute the overall QoS of Web services may produce inaccurate results, since they do not take correlations among QoS attributes into account. To resolve these problems, a Web service selection framework considering user’s preference priority is proposed, which incorporates a searching mechanism with QoS range setting to identify services satisfying the user’s QoS constraints. With the identified service candidates, based on the idea of Principal Component Analysis (PCA), an algorithm of Web service selection named PCA-WSS (Web Service Selection based on PCA) is proposed, which can eliminate the correlations among QoS attributes and compute the overall QoS of Web services accurately. After computing the overall QoS for each service, the algorithm ranks the Web service candidates based on their overall QoS and recommends services with top QoS values to users. Finally, the effectiveness and feasibility of our approach are validated by experiments, i.e. the selected Web service by our approach is given high average evaluation than other ones by users and the time cost of PCA-WSS algorithm is not affected acutely by the number of service candidates.

A QoS towards Dynamic Web services Recapitulation and Selection

Web services are the components, communicates via Internet or Web. Fundamental vision of the Web service is a brokerage system. The Recapitulation of Web service is an approach for the effective integration of distributed, heterogeneous and autonomous applications to build more Structured and value added services. Web services selection algorithms are required to find and select the best services. A QoS is a benchmark to select the best service for the task of composition. The QoS broker based web service selection plays an important role in service-oriented computing, where most of the applications are user specific QoS services. Here we propose a Broker based architecture for selection of web services. The importance of the web services selection algorithm is to maximize the QoS of the web services recapitulation using complex service provider's (CSP) QoS requirement parameters. This paper have discussed about different Web service Service-offers. We have classified the CSP’s requirements defined on the QoS and Service-offers based on its structure. This paper presents an efficient method to finding the suitable web service based on the consumer’s requirements along with QoS.

Study on Filter Algorithm of QoS-Based Fuzzy Multi-Attribute Web Service Composition

In this paper, an in-depth research has been done on the physical meaning and value features of the QoS attribute values under the definition of the functional attributes and non-functional attributes of Web services, giving the computation formulae and matching method expressing QoS composition as interval numbers, providing a more comprehensive and objective information matrix for fuzzy multi-attribute decision making. For multi-attributes fuzzy decision-making matrix with weight information known and the preference information of composition solution given in the form of interval numbers, calculating the overall attribute values, and sorting solutions by using the formula of probability degree, a QoS-driven multi-level composition Web Service selection algorithm is proposed, and simulation runs indicate the feasibility and effectiveness of the algorithm.

A Gravitational Search Algorithm for effective Web Service Selection for Composition with enhanced QoS in SOA

Web services selection and composition is a new software development paradigm to achieve service oriented computing. QoS of compound service is a key factor for satisfying the users‟ needs. The services selection algorithm based on quality of services is a combinatorial optimization problem. For Web services selection for composition based on QoS, the optimization algorithms can solve it well. Genetic Algorithm and Gravitational Search Algorithm are proposed to solve this issue. In order to meet the QoS requirements of consumers, this paper presents the QoS calculation of non functional requirements such as cost, availability, reliability and execution time. To verify the effectiveness in latency of Web Services selection the above two algorithms are compared. Results indicate the Gravitational Search Algorithm improves the latency over the Genetic algorithm.

A Web Service Selection Algorithm Based on Multiple QoS Registration Centers and Heterogeneous QoS Model

多QoS注册中心并且QoS模型异构给服务选择带来巨大困难。借鉴多属性群决策(MAGDM)理论的基本思想，该文提出一种解决上述难题的多注册中心和模型异构的Web服务选择算法(MRHQ_WSSA)。MRHQ_ WSSA算法能综合评估各QoS注册中心的QoS信息，从而获得QoS综合最优的服务组合计划。MRHQ_WSSA算法包括5个步骤：用户偏好规格化、群偏好确定、加权规格化决策矩阵、确定群理想方案、计算群贴近度。最后通过实验验证算法的优势和有效性。

An improved Particle Swarm Optimization Algorithm for QoS-aware Web Service Selection in Service Oriented Communication

QoS-aware Web Service Selection is a crucially important issue in Service Oriented Communication which enables communication by integrating communication web services over Internet. Because of the growing number of candidate web services that provide the same functionality but differ in Quality of Service (QoS), it brings more challenges to select a combination of composite services with optimal QoS performance, while satisfying users' QoS constraints. Here, an improved Particle Swarm Optimization Algorithm (iPSOA) is proposed to solve this problem. In order to make the algorithm more suitable for QoS-aware Web Service Selection, firstly we redefine the parameters, such as position, velocity and updating operations. In addition, a Non-Uniform Mutation (NUM) strategy is applied to the global best particle to enhance the population diversity on the purpose of overcoming the prematurity of PSOA and a non-uniform mutation function is also designed. Furthermore, the other two contributions are the Adaptive Wei...

Dynamic selection mechanism for quality of service aware web services

A web service is an interface of the software component that can be accessed by standard Internet protocols. The web service technology enables an application to application communication and interoperability. The increasing number of web service providers throughout the globe have produced numerous web services providing the same or similar functionality. This necessitates the use of tools and techniques to search the suitable services available over the Web. UDDI (universal description, discovery and integration) is the first initiative to find the suitable web services based on the requester's functional demands. However, the requester's requirements may also include non-functional aspects like quality of service (QoS). In this paper, the authors define a QoS model for QoS aware and business driven web service publishing and selection. The authors propose a QoS requirement format for the requesters, to specify their complex demands on QoS for the web service selection. The authors define a tree structure called quality constraint tree (QCT) to represent the requester's variety of requirements on QoS properties having varied preferences. The paper proposes a QoS broker based architecture for web service selection, which facilitates the requesters to specify their QoS requirements to select qualitatively optimal web service. A web service selection algorithm is presented, which ranks the functionally similar web services based on the degree of satisfaction of the requester's QoS requirements and preferences. The paper defines web service provider qualities to distinguish qualitatively competitive web services. The paper also presents the modelling and selection mechanism for the requester's alternative constraints defined on the QoS. The authors implement the QoS broker based system to prove the correctness of the proposed web service selection mechanism.

An improved Particle Swarm Optimization Algorithm for QoS-aware Web Service Selection in Service Oriented Communication

An improved Particle Swarm Optimization Algorithm for QoS-aware Web Service Selection in Service Oriented Communication

Quick convergence of genetic algorithm for QoS-driven web service selection

A novel quickly convergent population diversity handling genetic algorithm (CoDiGA) is presented for web service selection with global Quality-of-Service (QoS) constraints. CoDiGA is characterized by good stability and quick convergence. In CoDiGA, an enhanced initial population policy and an evolution policy are proposed based on population diversity and a relation matrix coding scheme. The integration of the two policies overcomes shortcomings resulting from randomicity of genetic algorithm, such as slow convergence, great variance among the running results, soaring overhead along with increasing size of composition. The simulation results on web service selection with global QoS constraints have shown that prematurity was overcomed effectively, and convergence and stability of genetic algorithm were improved greatly.

A Dynamic Web Services Selection Algorithm with QoS Global Optimal in Web Services Composition

As a new Web pattern, Web service has been rapidly developed in recent years. How to dynamically integrate the existent Web services to form a newly value-added and complex service to meet the requirement of different users is a popular research area. This paper presents an algorithm GODSS (global optimal of dynamic Web services selection) to resolve dynamic Web services selection with QoS global optimal in Web services composition. The essence of the algorithm is that the problem of dynamic Web Service selection with QoS global optimal is transformed into a multi-objective services composition optimization with QoS constraints. The theory of intelligent optimization of multi-objective genetic algorithm is utilized to produce a set of optimal Pareto services composition process with constraint principle by means of optimizing various objective functions simultaneously. Theoretical analysis and experimental results indicate the feasibility and efficiency of this algorithm.