Agent-Based Service-Oriented Computing and Applications
Bibliographic record
Abstract
Summary form only given. Service-oriented computing (SOC) is considered as a new computing paradigm after the object-oriented computing paradigm. It utilizes services as fundamental elements for applications/solutions. Services are autonomous platform-independent computational elements that can be described, published, discovered, orchestrated and programmed using XML for the purpose of developing massively distributed interoperable applications. Web services technology is part of the SOC paradigm and can be considered as an implementation of the SOC model. Web services are featured with application, platform and provider independence. They provide an appropriate approach for building open large-scale application environments. In such environments, services are not treated as isolated and one-time affairs but rather as elements of an interactive, dynamic and collaborative architecture. Service collaboration within or across environments is modelled in terms of supported transactions or processes that are subject to norms or protocols specified for certain business domains. Services are thereby orchestrated vertically within one environment, or horizontally across multiple environments. As a result, an individual environment streamlines services in terms of internal transactions while restrains its function scope to be highly specific to the targeted user group. Multiple environments collaborate in order to extend their business chains. Web services have been supported by major IT vendors through their commercial platforms such as Microsoft's .NET and SUN's J2EE. Web services have had quick evolution and broad acceptance. However, there are still a number of issues that limit the wide applications of Web services in industry. Current Web services technologies lack semantic description, generic service model, dynamic composition, and flexible cooperation strategies. Software agents have been proved to handle sophisticated interaction patterns. Agent-orientation is an appropriate design paradigm to enable automatic and dynamic collaborations, especially for e-Business systems with complex and distributed transactions. In services realization, software agents are very essential for the provision of a focused and cohesive set of active capabilities. Therefore, we envision a combination of agent and Web services technologies and strongly believe that we are on the right track towards an evolution of current SOC paradigm. Software agents can be one of the essential evolvements of Web services in that they are functional entities, instead of simple interaction delegations or communication proxies. The idea is to exploit agents' capabilities of proactive interactions to enhance Web services' behaviours. With such a computing paradigm, software components, each representing both a service and an agent, cooperatively or competitively interact to provide unified services in a specified environment, such as brokering, pricing and negotiation in an e-marketplace, as well as cross-enterprise environments, such as integration and cooperation in a virtual enterprise. We envision a Web service-based environment as a collection of economically motivated agent-based Web services. Software agents are implemented as services with different functionalities and roles. In fact, the dynamic agent-based behaviour model plus the Web service-based interoperable protocols can generate a flexible, reconfigurable and coordinated approach to perform business process management both across enterprises and within an enterprise. We have developed an agent-based service-oriented system architecture for manufacturing enterprise collaboration. In this system, each enterprise provides a number of Web services registered in a UDDI repository. The Web services are implemented by the AWS (agent-based Web services) technology with a built-in agent core. So, enterprises are equipped with negotiation ability with upper mediating agents. Moreover, upper mediating agents are also implemented as a network of AWSs on the Internet. The unification of software agents and Web services can be proposed at both the design level and the implementation level. At the design level, we encapsulate Web services into agent models so that each agent represents a service in its action and relation to the environment. In this sense, we treat a Web service as a semi-autonomous agent. On the other hand, Web services technologies are used to implement the external behaviours of software agents. Therefore, agents can be used to build high-level models with flexible interaction patterns, while Web services are more suitable for solving interoperability problems among heterogeneous applications across enterprises. At the implementation level, UDDI, WSDL and SOAP provide such capacities as discovery, deployment and communication, while specifications such as BPEL4WS provide service composition and process enactment. A software prototype system has been implemented for inter-enterprise manufacturing resource sharing. It demonstrates how the proposed agent-based service-oriented integration architecture can be used to establish a collaborative environment that provides dynamic resource scheduling services
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".