iMashup: a mashup-based framework for service composition

The Web has undergone a tremendous change from a primarily publication platform towards a participatory and"programmable"platform,where a large number of heterogeneous Web-delivered services(including SOAP and RESTful Web services,RSS and Atom feeds)are emerging.It results in the creation of Web mashup applications with rich user experiences.However,the integration of Web-delivered services is still a challenging issue.It not only requires the developers’tedious eforts in understanding and coordinating heterogeneous service types,but also results in the time-consuming development of user interfaces.In this paper,we propose the iMashup composition framework to facilitate mashup development and deployment.We provide a unified mashup component model for the common representation of heterogeneous Web-delivered service interfaces.The component model specifies necessary properties and behaviors at both business and user interface level.We associate the component model with semantically meaningful tags,so that mashup developers can fast understand the service capabilities.The mashup developers can search and put the proper mashup components into the Web browser based composition environment,and connect them by data flows based on the tag-based semantics.Such an integration manner might prevent some low-level programming eforts and improve the composition efciency.A series of experimental study are conducted to evaluate our framework.     

Research on dynamic business composition based on web service proxies

Web services-based business composition brings a number of advantages to the enterprise application development. How to select and compose the web services based on their functionality and QoS (Quality of Service) dynamically prove to be more and more important. In this paper we develop a proxy-based framework to compose Web services dynamically. The framework is featured with a QoS model, an effective service discovery and selection algorithms to facilitate the dynamic integration of Web services and management of abnormalities. Furthermore, a business process constructing method based on service slice is put forward to satisfy the users’ personalized requirements more effectively and flexibly. Our study concerns both functionality and QoS characteristics of Web services to identify the optimal business process solutions. A Complete case study is also included in this paper and the performance demonstrated that the framework and algorithms can provide a tangible and reliable solution to dynamic Web service composition and adaptation.     

Weighted fuzzy clustering for capability-driven service aggregation

Workflow design, mashup configuration, and composite service formation are examples where the capabilities of multiple simple services combined achieve a complex functionality. In this paper, we address the problem of limiting the number of required services that fulfill the required capabilities while exploiting the functional specialization of individual services. Our approach strikes a balance between finding one service that matches all required capabilities and having one service for each required capability. Specifically, we introduce a weighted fuzzy clustering algorithm that detects implicit service capability groups. The clustering algorithm considers capability importance and service fitness to support those capabilities. Evaluation based on a real-world data set successfully demonstrates the effectiveness of and applicability for service aggregation.     

基于Petri网的Web服务交互行为一致性检测方法

在复杂多变且不可预知的因特网环境中,Web组合服务的实际交互行为和它本身定义的规约之间的一致性是难以确保的。为了解决这个问题,提出了一种将服务组合实例的服务交互行为Petri网模型应用于交互行为一致性检测的方法。首先,提出了一个Web服务交互行为的运行时监控框架,从行为抽象和提取方法、服务交互行为的捕获机制以及交互行为一致性运行时检测方法三方面进行了详细介绍。还详细描述了基于服务交互行为Petri网模型的一致性检测机制。最后,对一致性检测方法的负载和性能进行了充分的评估。     

A reputation assessment model for trustful service recommendation

Nowadays, software systems are mainly Web front-based, Cloud-deployed and accessible by a wide audience over the Internet. These online systems commonly rely on Service-oriented Architecture principles, where they are built as orchestrations of RESTful (and in some rare cases as SOAP-based) services. Integrating new services in an existing orchestration is a challenging and risky task because trustworthiness of these services is not guaranteed throughout their lifetime. Reputation of services is a good indicator about the overall quality of services, because it reflects consumer satisfaction regarding the service-offered functionality and quality. Thus, reputation of services could be considered in the selection and recommendation of trustworthy services. In this paper, we present a framework for the management of web service reputation to conduct a better service recommendation. We present a reputation assessment model that aggregates fair user feedback ratings. The model includes a mechanism that prevents the introduction of malicious feedback ratings, by penalizing detected specious users. In addition, this framework includes a bootstrapping technique for estimating reputation of newcomer services based on neighbor similarity and initial advertised QoS. A set of experiments has been conducted to evaluate the effectiveness of the proposed framework. The results of these experiments highlighted the potential of our framework. These are presented at the end of the paper.     

Performance‐driven dynamic service selection

Modern software systems are increasingly built by integrating different services implemented by independent organizations and offered in an open service marketplace. In such environment, multiple providers may compete with each other by publishing services that provide the same functionality, and export the same interface, but differ in the offered QoS and in particular in the offered performance. Clients and service integrators may therefore dynamically select the most efficient services that satisfy their requirements among the competing alternatives. Service selection may be performed by clients by following different strategies, which may ultimately affect the overall quality of service invocations. In this paper, we address the problem of analyzing and comparing different service selection strategies based on a framework that supports performance estimates. We report on quantitative analyses through simulations, highlighting advantages and limitations of each strategy. Copyright © 2014 John Wiley & Sons, Ltd.     

Per-flow optimal service selection for Web services based processes

With the development of the Service-Oriented Computing (SOC) paradigm, flexible business processes can be defined from independently developed services. Multiple services corresponding to the same functionality but characterized by different Quality of Service (QoS) attributes can be offered by different service providers and the best set of Web services can be selected at run-time in order to maximize the QoS for end users.In the literature many approaches have been proposed for the optimal service selection which is usually performed on a per-request basis, i.e., considering a single process invocation. In this paper we propose a broker-based framework which solves the optimal service selection on a per-flow basis. Multiple applications, defined as different BPEL processes are considered at the same time and multiple requests to the same process are optimized concurrently.Service selection is formulated as a constrained non-linear multi-criteria optimization problem and an heuristic algorithm is proposed to determine a scalable and efficient solution.A comparison with top performing state-of-the-art approaches for a number of different scenarios of interest is also provided. Results show that the overall optimization time reduction which can be achieved by our solution is proportional to the system incoming workload. Order of magnitudes optimization time improvements can be obtained if compared to alternative methods. Moreover, our solution is robust to workload prediction uncertainty.     

Conceptual framework and architecture for service mediating workflow management

This paper proposes a three-layer workflow concept framework to realize workflow enactment flexibility by dynamically binding activities to their implementations at run time. A service mediating layer is added to bridge business process definition and its implementation. Based on this framework, we propose an extended workflow management systems architecture, in which service contracting layer, service binding layer and service invocation layer are extensions to support the proposed service mediating concept. According to an enactment specification, different instances of the same activity can be bound to different services to achieve enactment flexibility. The conceptual framework and architecture together provide a comprehensive approach to flexible service enactment in B2B collaborative settings.     

Web service API recommendation for automated mashup creation using multi-objective evolutionary search

Modern software development builds on external Web services reuse as a promising way that allows developers delivering feature-rich software by composing existing Web service Application Programming Interfaces, known as APIs. With the overwhelming number of Web services that are available on the Internet, finding the appropriate Web services for automatic service composition, i.e., mashup creation, has become a time-consuming, difficult, and error-prone task for software designers and developers when done manually. To help developers, a number of approaches and techniques have been proposed to automatically recommend Web services. However, they mostly focus on recommending individual services. Nevertheless, in practice, service APIs are intended to be used together forming a social network between different APIs, thus should be recommended collectively. In this paper, we introduce a novel automated approach, called SerFinder, to recommend service sets for automatic mashup creation. We formulate the service set recommendation as a multi-objective combinatorial problem and use the non-dominated sorting genetic algorithm (NSGA-II) as a search method to extract an optimal set of services to create a given mashup. We aim at guiding the search process towards generating the adequate compromise among three objectives to be optimized (i) maximize services historical co-usage, (ii) maximize services functional matching with the mashup requirements, and (iii) maximize services functional diversity. We perform a large-scale empirical experiment to evaluate SerFinder on a benchmark of real-world mashups and services. The obtained results demonstrate the effectiveness of SerFinder in comparison with recent existing approaches for mashup creation and services recommendation. The statistical analysis results provide an empirical evidence that SerFinder, significantly outperforms four state-of-the-art widely-used multi-objective search-based algorithms as well as random search.     

A flexible service selection for executing virtual services

With the adoption of a service-oriented paradigm on the Web, many software services are likely to fulfil similar functional needs for end-users. We propose to aggregate functionally equivalent software services within one single virtual service, that is, to associate a functionality, a graphical user interface (GUI), and a set of selection rules. When an end user invokes such a virtual service through its GUI to answer his/her functional need, the software service that best responds to the end-user’s selection policy is selected and executed and the result is then rendered to the end-user through the GUI of the virtual service. A key innovation in this paper is the flexibility of our proposed service selection policy. First, each selection policy can refer to heterogeneous parameters (e.g., service price, end-user location, and QoS). Second, additional parameters can be added to an existing or new policy with little investment. Third, the end users themselves define a selection policy to apply during the selection process, thanks to the GUI element added as part of the virtual service design. This approach was validated though the design, implementation, and testing of an end-to-end architecture, including the implementation of several virtual services and utilizing several software services available today on the Web.     

Efficient and reliable service selection for heterogeneous distributed software systems

The service-oriented paradigm is emerging as a new approach to heterogeneous distributed software systems composed of services accessed locally or remotely by middleware technology. How to select the optimal composited service from a set of functionally equivalent services with different quality of service (QoS) attributes has become an active focus of research in the service community. However, existing middleware solutions or approaches are inefficient as they search all solution spaces. More importantly, they inherently neglect QoS uncertainty owing to the dynamic network environment. In this paper, based on a service composition middleware framework, we propose an efficient and reliable service selection approach that attempts to select the best reliable composited service by filtering low-reliability services through the computation of QoS uncertainty. The approach first employs information theory and probability theory to abandon high-QoS-uncertainty services and downsize the solution space. A reliability fitness function is then designed to select the best reliable service for composited services. We experimented with real-world and synthetic datasets and compared our approach with other approaches. Our results show that our approach is not only fast, but also finds more reliable composited services.     

G-TOPSIS: a cloud service selection framework using Gaussian TOPSIS for rank reversal problem

The dynamic resource requirement of applications has forced a large number of business organizations to join the cloud market and provide cloud services. It has posed a challenge for cloud users to select the best service providers and to minimize losses occurring due to its improper selection. This paper aims to propose a robust rank reversal technique for order of preference by similarity to ideal solution (TOPSIS) method based on Gaussian distribution and used to develop a cloud service selection framework. The proposed framework ranks cloud services based on the quality of services provided by cloud service providers and cloud user’s priority. A case study is performed on a real dataset obtained from CloudHarmony to show the effectiveness and correctness of the proposed framework. The results obtained demonstrate that the proposed framework ranks cloud services similar to TOPSIS-based frameworks. A sensitivity analysis has also been performed to check its robustness in six different cases causing rank reversal and found that the proposed framework is robust to handle rank reversal phenomenon in all the scenarios in comparison with other studies available in the literature.

     

Virtual machine support for zero‐loss Internet service recovery and upgrade

Software is critical for Internet service availability since an Internet service may become unavailable due to software faults or software maintenance. In this paper, we propose a framework to allow zero‐loss recovery and online maintenance for Internet services. The framework is based on the virtual machine (VM) technology and a connection migration technique called FT‐TCP. It can recover transient application/operating system faults and it allows fault recovery and online maintenance on a single host. The framework substantially enhances FT‐TCP so that it can be run efficiently in the VM environment. Specifically, we propose techniques to reduce the inter‐VM switches and communication. Moreover, we propose service‐specific optimizations to reduce the recovery time of FT‐TCP. Finally, the framework provides an interface for the service designers to implement more service‐specific optimizations. The framework was implemented by modifying an open source VM monitor, Xen, and the Linux kernel running on top of Xen. The effectiveness and efficiency of the framework were evaluated by running two Internet services, WWW proxy and FTP, on the proposed framework and measuring the impact on their performance. According to the experimental results, our approach causes only slight performance overhead (i.e. less than 4%) and memory overhead (i.e. less than 750 KB) for both the services. Copyright © 2007 John Wiley & Sons, Ltd.     

Reo + mCRL2 : A framework for model-checking dataflow in service compositions

The paradigm of service-oriented computing revolutionized the field of software engineering. According to this paradigm, new systems are composed of existing stand-alone services to support complex cross-organizational business processes. Correct communication of these services is not possible without a proper coordination mechanism. The Reo coordination language is a channel-based modeling language that introduces various types of channels and their composition rules. By composing Reo channels, one can specify Reo connectors that realize arbitrary complex behavioral protocols. Several formalisms have been introduced to give semantics to Reo. In their most basic form, they reflect service synchronization and dataflow constraints imposed by connectors. To ensure that the composed system behaves as intended, we need a wide range of automated verification tools to assist service composition designers. In this paper, we present our framework for the verification of Reo using the mCRL2{{\tt mCRL2}} toolset. We unify our previous work on mapping various semantic models for Reo, namely, constraint automata, timed constraint automata, coloring semantics and the newly developed action constraint automata, to the process algebraic specification language of mCRL2{{\tt mCRL2}}, address the correctness of this mapping, discuss tool support, and present a detailed example that illustrates the use of Reo empowered with mCRL2{{\tt mCRL2}} for the analysis of dataflow in service-based process models.     

Online role mining for context-aware mobile service recommendation

Finding and recommending suitable services for mobile devices are increasingly important due to the popularity of mobile Internet. While recent research has attempted to use role-based approaches to recommend services, role discovery is still an ongoing research topic. Using role-based approaches, popular mobile services can be recommended to other members in the same role group in a context- dependent manner. This paper proposes several role mining algorithms, to suit different application requirements, that automatically group users according to their interests and habits dynamically. Most importantly, we propose an online role mining algorithm that can discover role patterns efficiently and incrementally. Finally, we present a complete, question-based framework that can efficiently perform role mining for context-aware service recommendation in a mobile environment—where a device may not be always connected to the server and/or scalability of the role mining algorithm running on the server is critical.