Yue Zhang

Bio: Yue Zhang is an academic researcher from University of California, Irvine. The author has contributed to research in topics: Knapsack problem & Heuristic (computer science). The author has an hindex of 1, co-authored 1 publications receiving 1201 citations.

Efficient algorithms for Web services selection with end-to-end QoS constraints

Abstract: Service-Oriented Architecture (SOA) provides a flexible framework for service composition Using standard-based protocols (such as SOAP and WSDL), composite services can be constructed by integrating atomic services developed independently Algorithms are needed to select service components with various QoS levels according to some application-dependent performance requirements We design a broker-based architecture to facilitate the selection of QoS-based services The objective of service selection is to maximize an application-specific utility function under the end-to-end QoS constraints The problem is modeled in two ways: the combinatorial model and the graph model The combinatorial model defines the problem as a multidimension multichoice 0-1 knapsack problem (MMKP) The graph model defines the problem as a multiconstraint optimal path (MCOP) problem Efficient heuristic algorithms for service processes of different composition structures are presented in this article and their performances are studied by simulations We also compare the pros and cons between the two models

QoS-Aware Web Service Recommendation by Collaborative Filtering

Abstract: With increasing presence and adoption of Web services on the World Wide Web, Quality-of-Service (QoS) is becoming important for describing nonfunctional characteristics of Web services. In this paper, we present a collaborative filtering approach for predicting QoS values of Web services and making Web service recommendation by taking advantages of past usage experiences of service users. We first propose a user-collaborative mechanism for past Web service QoS information collection from different service users. Then, based on the collected QoS data, a collaborative filtering approach is designed to predict Web service QoS values. Finally, a prototype called WSRec is implemented by Java language and deployed to the Internet for conducting real-world experiments. To study the QoS value prediction accuracy of our approach, 1.5 millions Web service invocation results are collected from 150 service users in 24 countries on 100 real-world Web services in 22 countries. The experimental results show that our algorithm achieves better prediction accuracy than other approaches. Our Web service QoS data set is publicly released for future research.

Combining global optimization with local selection for efficient QoS-aware service composition

Abstract: The run-time binding of web services has been recently put forward in order to support rapid and dynamic web service compositions. With the growing number of alternative web services that provide the same functionality but differ in quality parameters, the service composition becomes a decision problem on which component services should be selected such that user's end-to-end QoS requirements (e.g. availability, response time) and preferences (e.g. price) are satisfied. Although very efficient, local selection strategy fails short in handling global QoS requirements. Solutions based on global optimization, on the other hand, can handle global constraints, but their poor performance renders them inappropriate for applications with dynamic and real-time requirements. In this paper we address this problem and propose a solution that combines global optimization with local selection techniques to benefit from the advantages of both worlds. The proposed solution consists of two steps: first, we use mixed integer programming (MIP) to find the optimal decomposition of global QoS constraints into local constraints. Second, we use distributed local selection to find the best web services that satisfy these local constraints. The results of experimental evaluation indicate that our approach significantly outperforms existing solutions in terms of computation time while achieving close-to-optimal results.

Selecting skyline services for QoS-based web service composition

Abstract: Web service composition enables seamless and dynamic integration of business applications on the web. The performance of the composed application is determined by the performance of the involved web services. Therefore, non-functional, quality of service aspects are crucial for selecting the web services to take part in the composition. Identifying the best candidate web services from a set of functionally-equivalent services is a multi-criteria decision making problem. The selected services should optimize the overall QoS of the composed application, while satisfying all the constraints specified by the client on individual QoS parameters. In this paper, we propose an approach based on the notion of skyline to effectively and efficiently select services for composition, reducing the number of candidate services to be considered. We also discuss how a provider can improve its service to become more competitive and increase its potential of being included in composite applications. We evaluate our approach experimentally using both real and synthetically generated datasets.

Handbook of Cloud Computing

Abstract: Cloud computing has become a significant technology trend Experts believe cloud computing is currently reshaping information technology and the IT marketplace The advantages of using cloud computing include cost savings, speed to market, access to greater computing resources, high availability, and scalability Handbook of Cloud Computing includes contributions from world experts in the field of cloud computing from academia, research laboratories and private industry This book presents the systems, tools, and services of the leading providers of cloud computing; including Google, Yahoo, Amazon, IBM, and Microsoft The basic concepts of cloud computing and cloud computing applications are also introduced Current and future technologies applied in cloud computing are also discussed Case studies, examples, and exercises are provided throughout Handbook of Cloud Computing is intended for advanced-level students and researchers in computer science and electrical engineering as a reference book This handbook is also beneficial to computer and system infrastructure designers, developers, business managers, entrepreneurs and investors within the cloud computing related industry

Collaborative Web Service QoS Prediction via Neighborhood Integrated Matrix Factorization

Abstract: With the increasing presence and adoption of web services on the World Wide Web, the demand of efficient web service quality evaluation approaches is becoming unprecedentedly strong. To avoid the expensive and time-consuming web service invocations, this paper proposes a collaborative quality-of-service (QoS) prediction approach for web services by taking advantages of the past web service usage experiences of service users. We first apply the concept of user-collaboration for the web service QoS information sharing. Then, based on the collected QoS data, a neighborhood-integrated approach is designed for personalized web service QoS value prediction. To validate our approach, large-scale real-world experiments are conducted, which include 1,974,675 web service invocations from 339 service users on 5,825 real-world web services. The comprehensive experimental studies show that our proposed approach achieves higher prediction accuracy than other approaches. The public release of our web service QoS data set provides valuable real-world data for future research.