Service discovery in Web service infrastructure must consider abstract processes to guarantee successful business interactions with the matched services. Unfortunately, matchmaking process annotations requires a significant processing effort, thus, finding relevant service providers in a large collection is time consuming and requires more efficient access methods than sequential scanning. The paper presents an approach supporting more efficient querying of abstract processes by introducing an abstraction to reduce the computational complexity of the comparison operation. Experimental studies on a collection of over 800 abstract business processes derived from the RosettaNet PIP specification show that our approach outperforms naive sequential scanning by up to an order of magnitude.
T-learning - the provision of educational services over interactive digital TV - is emerging as a important medium to create opportunities for learning at home. In this paper, we elaborate on a framework for the development and deployment of collaborative t-learning services, presenting an architecture that allows distributing the logic of a service, a way to define complex interaction patterns among users and a network infrastructure that provides adequate support for the communication needs.
Owing to the fast growth of Internet technology, enterprises are facing crucial challenges from both competitors and consumers in the global market. In order to get survived, forming strategic supply chain alliances and utilizing the Internet technology to establish a quick response (QR) system (also called the efficient customer response (ECR) system) become as the common practice for enterprises in terms of cost reduction and efficiency improvement. This paper first presents an Internet-based QR framework for a perishable goods supply chain alliance. Secondly, with the aim of optimizing the expected QR alliance profit, a dynamic frequency-based supply and distribution (DF-SD) algorithm is developed under the constraints of short food freshness period, limited distribution centre capacity, contract violation penalty, and uncertain supply rate. The DF-SD algorithm is composed of a linear programming (LP) model and an extended genetic algorithm (GA) to generate the optimal supply and distribution strategy for all members in the perishable goods supply chain. Simulation results show that the proposed QR approach successfully outperforms the traditional fixed-frequency approach in terms of both the solution quality as well as computation time efficiency.
Web services are a key technology for automating inter-organizational interactions. Enterprises can externalise parts of their business processes using them. Then they can dynamically combine existing services to offer value added composite services (CS). One remaining problem is how to ensure a correct composition and a reliable execution of a CS with regards to partners' transactional requirements. In this paper, we present a transactional approach to ensure the failure atomicity of CS required by partners. Partners specify their CS and the requested failure atomicity. Then, we use a set of rules to validate the composite service with regards to designers' transactional requirements.
For multinational companies, buying and selling products worldwide is part of their every day business. Thus they have to deal with receivables and payables denominated in foreign currencies, which have to be hedged against foreign currency risk using derivative foreign exchange contracts. In the past this task has strongly relied on voice based broking. However, with Internet technology, online marketplaces for trading foreign exchange emerged offering access to the liquidity of a global market. Still companies are reluctant when deciding about the deployment of this new trading channel, knowing that it will only become valuable when seamlessly integrated into the corporate's foreign exchange trading process. In this work we present a Web service based straight through processing implementation and evaluate the users' acceptance of the integrated online marketplace.
In this paper we discuss the Recommendz recommender system. This domain-independent system combines the advantages of collaborative and content-based filtering in a novel way. By allowing users to provide feedback not only about an item as a whole, but also properties of an item that motivated their opinion, increased performance seems to be achieved. The features used to describe items are specified by the users of the system rather than predetermined using manual knowledge-engineering. We describe a method for combining descriptive features and simple ratings, and provide a performance analysis.
An agent-based architecture of an active digital library (DL) is first described, to illustrate how electronic service provision can be supported through the use of agents. The use of mobile agents is presented as a key enabler for allowing services to be combined from a variety of providers. Load balancing approaches are then used to illustrate how particular performance criteria can be achieved in service provision. Extrapolation of the approach to the general service-oriented computing model is briefly discussed.
This paper presents a novel hybrid two-phase peer evaluation model for P2P e-commerce systems, which consists of both peer trust evaluation and peer offer evaluation. Meanwhile, the peer trust evaluation phase consists of two phases: peer transaction trust evaluation and peer certificate trust evaluation.
In order to improve a quality of filtering services, an exploration that is based on a usage of knowledge, being hidden in numerous already processed requests, has to be performed. Small scale applicability and ignoring a necessity to control the exploration are major drawbacks for many existed systems which try to explore new information areas. The essence of the proposed collaborative guided exploration is in its comprehensive control over a level of a request adaptation and in its applicability on huge spaces, where filtering requests are defined. The applicability of the presented exploration is illustrated in one travel finder system (URLAUB) and in one personal information assistant (PIA). Experimental results show that filtering requests, for which one good neighbourhood exists, can significantly be improved by adding new relevant words.
Although previous studies have achieved a great deal on the local decision areas including inventory policies, vendor selection, production scheduling, etc., and the strategic problems, e.g. networks design, simulation and prediction of the supply chain as a whole, few attempts have been focused on the integrated solution for supply chain operational management. As the structure of multi-agent systems (MAS) inherently meets the requirements of autonomy and decentralization for supply chains, we propose a multi-agent-based model of planning, scheduling and execution that is capable of supporting the resource coordination between the self-interested agents through a combinatorial auction mechanism. And a general framework of ASCMS (agile supply chain management system) is presented as the background. To facilitate the functions of this system, the components of various agents and the negotiation process are also discussed in this paper.
In this paper we present AVATAR, a recommender of personalized TV contents, for which an open multi-agent architecture is proposed. This tool uses different knowledge inference strategies, even though we focus on the description of one of them, the naive Bayesian classifiers. Standardization is a key issue to achieve wide deployment in this kind of systems. So, the described recommendation tool has been conceived as an application conforming to multimedia home platform (MHP) standard, to be distributed in the broadcast transport stream that will be tuned by each user's receiver. Also, the TV-Anytime specification has been used referred to the description of contents, the users preferences and their activity logs.
The development and wider use of wireless networks and mobile devices has led to novel pervasive computing environments which pose new problems for software rights management and enforcement on resource-constrained and occasionally connected devices. Software vendors are, however, still applying old usage rights models to a platform where application rights will be specified, managed and distributed in new and different ways. The characteristics of pervasive environments, such as occasional connectivity, require the introduction of more flexible usage rights models, such as audit-based model, that do not assume the availability of network connections. In this paper we describe a pervasive application rights management architecture for both desktop and mobile applications that provides an integrated platform for the specification, generation, delivery, and management of application usage rights based on Web services standards. We also introduce flexible usage rights models required by pervasive environments that can be embedded in target applications using aspect-oriented technology.
Mediating privacy mechanisms on the client-side aid in next generation e-transformation as they enhance users' perception of online trust in an organization. We propose a collaboration, between a context agent and a P3P agent, which results in the application of context-specific privacy rules during a user's electronic commerce transaction with an organization's Web site or Web service. The context agent manages dynamic changes of the context, inform the user about the current privacy-related context for decision support, and automatically generate user preferences. Fully compliant to the P3P privacy platform, the context management system supports the storage, index, retrieval, and switch of user contexts. Test cases using real Web sites' P3P policies demonstrate the functionality and utility of the context manager agent. Delays are in the range of less than one second to 7 seconds depending on activities such as a context switch or P3P comparison.
The need for coordinated material flow in supply chains is essential for the competitiveness of manufacturing firms. A hierarchical coordination is not applicable for each supply chain. A collaboration between entities is required to meet future challenges. Besides appropriate planning concepts an IT solution is a major challenge. Multi-agent systems (MAS) are an enabler for a decentralized coordination process. The evolvement of appropriate planning methods makes MAS interesting for collaborative supply chain management (SCM). Nevertheless, the user should be seen as the supply chain engineer, holding the knowledge to create the collaborative supply chain processes. Therefore, the user has to be integrated in the IT solution. A configurable MAS, based on generic components, satisfies this requirement so that MAS can easily be adapted to the changing processes and environment by the user. This paper presents a concept of a configurable MAS and a prototype of a MAS-Editor for collaborative production planning.
Web services are modular web applications that can be independently deployed and invoked by other software or services on the web. This offers enterprises the capability to integrate in-house business services with external Web services to conduct complex business transactions. The integration efficiency and flexibility are critical for services composition. For Web services providing a similar functionality, Quality of Service (QoS) is the main factor to differentiate them. The overall QoS of a business process must meet a user's requirement. In this paper, we propose a broker-based framework to facilitate dynamic integration and adaptation of QoS-aware Web services with end-to-end QoS constraints. The key functions of a dynamic broker include service collection, selection, composition and adaptation. Our study considers both functional and QoS characteristics of Web services to identify the optimal business process solutions.
Web service composition is now seen as a focal point of research, especially as mechanisms for the coordination of distributed tasks are acquiring more importance. Models such as BPEL4WS can cater for local and centralised coordination. There is, however, a need to reconcile different technologies on a wider scale. This requires the development of efficient and flexible frameworks in order to ensure the optimal use and coordination of distributed applications. The work presented in this paper is concerned with the development of a compositional framework, which brings together grid services, Web services and semantic Web technology within a BPEL4WS platform. It is aimed at enhancing BPEL4WS by allowing for the hybrid composition of Web services and grid services, and by incorporating dynamic binding through agent mediation. The efficient management of workflows afforded by BPEL4WS is combined with the versatility of agent technology. An agent-based system, called SOA, was developed to support the framework.
The quality of the results produced by personalized e-service applications like product recommenders, buying advisory applications, or product configurators is strongly determined by the accuracy of the system's estimate of the individual customer's real needs and preferences. In particular in domains where customers cannot be classified automatically, e.g., based on past buying behavior, these needs have to be interactively elicited by questioning the user. In many existing systems only a "one-style-fits-all" approach based on static fill-out forms is chosen. However, this does not take the user's background or capabilities into account, which consequently leads to a poor quality of the acquired user model. In this paper, we show how extensive personalization of the user preference elicitation process itself can significantly improve the accuracy of interactively acquired user models. A comprehensive view on adaptation and personalization opportunities in the elicitation process is developed and corresponding examples for the domain of interactive buying advisory are given. The presented personalization and adaptation techniques are implemented in a domain-independent software framework for building interactive advisory applications. We describe specific architectural requirements for such a system and discuss results from various real-world applications.
E-finance refers to financial systems using the emerging Internet and e-commerce systems. Thanks to the worldwide interest in Web-based e-services, we find Web-services being ushered into financial markets that are sensitive to security concerns. This research was carried out to investigate the effectiveness of emerging security features of Web services in the context of financial markets. In the process we have developed a new evaluation framework (SEFAN) for the security of e-finance systems. This paper presents SEFAN model and its evaluation based on contextual interview of experts.
Today many e-learning systems achieve high standards in delivering online courses via Web technologies and database system. However, these systems are constrained by rigid data model or schema that was pre-defined in the database to provide data storage structure for contents in e-learning applications. In the development of database driven e-learning system, the schema is crucial in analysing the data requirement for the system. However, many disadvantages are the results of system being developed on top of a static data model structure. The most concern issue includes the inflexibility of the data model that leads to unalterable contents data structure and its layout format, because the attributes in the data model are expected to be hard coded during the development in most cases. To avoid such inflexibility and improve the performance in the e-learning system, this paper introduces an approach of generic data model scheme in the database structure and interface-design toolkits, which allow the users to make modifications on the data structure and the system has the ability to adapt these changes. It achieves the adaptability, extensibility and reusability of database structure in the e-learning system.
Although management of resources is essential for realizing a computational grid, providing efficient resource allocation mechanism is a complex undertaking. Since providers and consumers of grid resource may be independent bodies, negotiation among these participants is necessary. This work suggests that market-driven agents (MDAs) are appropriate mechanisms for grid resource negotiation. MDAs are negotiation agents designed with the flexibility of (i) making adjustable amounts of concession taking into consideration market rivalry, outside options, and time preferences and (ii) relaxing trade expectation in the face of intense pressure. This paper argues that MDAs are appropriate tools for grid resource negotiation because they possess desirable properties such as having stable strategies, making prudent compromises and optimizing utilities, adapting to changes in market conditions, and are more likely in successfully reaching consensus.
