Service-oriented computing : agents, semantics, and engineering : AAMAS 2007 International Workshop, SOCASE 2007, Honolulu, HI, USA, May 14, 2007 : proceedings

Executing Semantic Web Services with a Context-Aware Service Execution Agent.- An Effective Strategy for the Flexible Provisioning of Service Workflows.- Using Goals for Flexible Service Orchestration.- An Agent-Based Approach to User-Initiated Semantic Service Interconnection.- A Lightweight Agent Fabric for Service Autonomy.- Semantic Service Composition in Service-Oriented Multiagent Systems: A Filtering Approach.- Towards a Mapping from BPMN to Agents.- Associated Topic Extraction for Consumer Generated Media Analysis.- An MAS Infrastructure for Implementing SWSA Based Semantic Services.- A Role-Based Support Mechanism for Service Description and Discovery.- WS2JADE: Integrating Web Service with Jade Agents.- Z-Based Agents for Service Oriented Computing

Study of SOA Component Dynamic Scheduling Based on Mobile Agent Coalition

Service-oriented components differ greatly with the traditional ones in the Service-Oriented Architecture. The ways of scheduling components seamlessly according to the agile computing needs to fit the e-business requirements is the key technology in the highly distributed, paralleled environment. In this paper, Based on the Multi-Agent Coalition, a new service-oriented component dynamic scheduling model is proposed, including the Multi-Agent Organization to schedule and coordinate the component assembly, the design of virtual execution task list table and self-learning algorithm, the definition of the Services component model, and the mechanism of collaboration Agents to search, discovery, concurrent schedule, dynamic assembly when execution in an heterogeneous network environment. To a large extent, the thesis solves the traditional problem of over-emphasis on centralized control logic, which leads to lacking flexibility in e-Business computing presently, and helps e-business service-oriented components become more adaptive, mobility and intelligence

Cloud Computing Integrated into Service-Oriented Multi-Agent Architecture

The main objective of Cloud Computing is to provide software, services and computing infrastructures carried out independently by the network. This concept is based on the development of dynamic, distributed and scalable software. In this way there are Service-Oriented Architectures (SOA) and agent frameworks which provide tools for developing distributed systems and multiagent systems that can be used for the establishment of cloud computing environments. This paper presents CISM@ (Cloud computing Integrated into Service-Oriented Multi-Agent) architecture set on top of the platforms and frameworks by adding new layers for integrating a SOA and Cloud Computing approach and facilitating the distribution and management of functionalities

Cloud Computing with Intelligent Agents to Support Service Oriented System Control and Management

the past few years, Cloud computing has becoming one of the revolutionary technologies in ICT which grows in both popularity and importance, both in industry and in academic domain. More and more private companies, government organizations and institutions are convinced and happy to promote Cloud to improve both connectivity and instant social ability. For IT services and solutions for business, Cloud-based platform promises to offer better business intelligence and productive experience by using unified communications, consistent collaborated data and service management. It is well believed that Cloud Computing will also bring a revolution in the healthcare IT sector along with other ICT business. To exploit Cloud computing productivity potential, this paper focuses on adopting Cloud computing technologies with agent-based solutions to support service oriented system control and management. The on-going research and practice demonstrates an application to the management of community care provision, which shows transforming to Software-as-a-Service (Saas) with the combination of a private healthcare cloud and integrated agents can improve business efficiency by providing flexible services scheduling, smarter health care services control and management

Multi-agent based supply chain management with dynamic reconfiguration capability

Supply chain management (SCM) has received increased attention in a globally challenging environment as companies face the necessity to improve customer service and maximize profit. Therefore, dynamic reconfiguration capability is vital for supply chain management to respond to changing customer requirements and operating environments. On the other hand, for its flexible and autonomous characteristics, multi-agent systems are a viable technology for SCM, and have been widely applied in SCM. To this end, dynamic reconfiguration in agent-based SCM systems is proposed from autonomy oriented computing point of view. The performance of agent-based SCM with dynamic reconfiguration is evaluated under a modified TAC SCM scenario. With a dynamic reconfigurable SCM system, new products and processes can be introduced with considerably less expense and ramp-up time.<br /

An agent-based service-oriented approach to evolving legacy software systems into a pervasive computing environment.

This thesis focuses on an Agent-Based Service-Oriented approach to evolving legacy system into a Pervasive Computing environment. The methodology consists of multiple phases: using reverse engineering techniques to comprehend and decompose legacy systems, employing XML and Web Services to transform and represent a legacy system as pervasive services, and integrating these pervasive services into pervasive computing environments with agent based integration technology. A legacy intelligent building system is used as a case study for experiments with the approach, which demonstrates that the proposed approach has the ability to evolve legacy systems into pervasive service environments seamlessly. Conclusion is drawn based on analysis and further research directions are also discussed

Towards self-organized service-oriented multi-agent systems

The demand for large-scale systems running in complex and even chaotic environments requires the consideration of new paradigms and technologies that provide flexibility, robustness, agility and responsiveness. Multiagents systems is pointed out as a suitable approach to address this challenge by offering an alternative way to design control systems, based on the decentralization of control functions over distributed autonomous and cooperative entities. However, in spite of their enormous potential, they usually lack some aspects related to interoperability, optimization in decentralized structures and truly self-adaptation. This paper discusses a new perspective to engineer adaptive complex systems considering a 3-layer framework integrating several complementary paradigms and technologies. In a first step, it suggests the integration of multi-agent systems with service-oriented architectures to overcome the limitations of interoperability and smooth migration, followed by the use of technology enablers, such as cloud computing and wireless sensor networks, to provide a ubiquitous and reconfigurable environment. Finally, the resulted service-oriented multi-agent system should be enhanced with biologically inspired techniques, namely self-organization, to reach a truly robust, agile and adaptive system

Utility-Based Mechanism for Structural Self-Organization in Service-Oriented MAS

Structural relations established among agents influence the performance of decentralized service discovery process in multiagent systems. Moreover, distributed systems should be able to adapt their structural relations to changes in environmental conditions. In this article, we present a service-oriented multiagent systems, where agents initially self-organize their structural relations based on the similarity of their services. During the service discovery process, agents integrate a mechanism that facilitates the self-organization of their structural relations to adapt the structure of the system to the service demand. This mechanism facilitates the task of decentralized service discovery and improves its performance. Each agent has local knowledge about its direct neighbors and the queries received during discovery processes. With this information, an agent is able to analyze its structural relations and decide when it is more appropriate to modify its direct neighbors and select the most suitable acquaintances to replace them. The experimental evaluation shows how this self-organization mechanism improves the overall performance of the service discovery process in the system when the service demand changesThis work is partially supported by the Spanish Ministry of Science and Innovation through grants CSD2007-0022 (CONSOLIDER-INGENIO 2010), TIN2012-36586-C03-01, TIN2012-36586-C03-01, TIN2012-36586-C03-02, PROMETEOII/2013/019, and FPU grant AP-2008-00601 awarded to E. Del Val.Del Val Noguera, E.; Rebollo Pedruelo, M.; Vasirani, M.; Fernández, A. (2014). Utility-Based Mechanism for Structural Self-Organization in Service-Oriented MAS. ACM Transactions on Autonomous and Adaptive Systems. 9(3):1-24. https://doi.org/10.1145/2651423S12493Sherief Abdallah and Victor Lesser. 2007. 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A survey on quality of service support on middelware-based distributed messaging systems used in multi agent systems

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-19934-9_10Messaging systems are widely used in distributed systems to hide the details of the communications mechanism to the multi agents systems. However, the Quality of Service is treated in different way depending on the messaging system used. This article presents a review and further analysis of the quality of service treatment in the mainly messaging systems used in distributed multi agent systems. The review covers the issues related to the purpose of the functions provided and the scope of the quality of service offered by every messaging system. We propose ontology for classifying and decide which parameters are relevant to the user. The results of the analysis and the ontology can be used to select the most suitable messaging system to distributed multi agent architecture and to establish the quality of service requirements in a distributed system.The study described in this article is a part of the coordinated project SIDIRELI: Distributed Systems with Limited Resources. Control Kernel and Coordination. Education and Science Department, Spanish Government and European FEDER found. CICYT: MICINN: DPI2008-06737-C02-01/02.Poza-Lujan, J.; Posadas-Yagüe, J.; Simó Ten, JE. (2011). A survey on quality of service support on middelware-based distributed messaging systems used in multi agent systems. En International Symposium on Distributed Computing and Artificial Intelligence. Springer. 77-84. https://doi.org/10.1007/978-3-642-19934-9_10S7784Gaddah, A., Kunz, T.: A survey of middleware paradigms for mobile computing. Technical Report SCE-03-16. Carleton University Systems and Computing Engineering (2003)Foundation for Intelligent Physical Agents, http://www.fipa.org/Java Message Service Specification, http://java.sun.com/products/jms/docs.htmlCommon Object Request Broker Architecture, http://www.corba.org/Data Distribution Service, http://portals.omg.org/dds/Java Agent DEvelopment Framework, http://jade.tilab.com/Agent Oriented Software Pty Ltd., JACK Intelligent Agents: User Guide (1999)Nwana, H., Ndumu, D., Lee, L., Collis, J.: ZEUS: A tool-kit for building distributed multi-agent systems. Applied Artifical Intelligence Journal 13(1), 129–186 (1999)Perdikeas, M.K., Chatzipapadopoulos, F.G., Venieris, I.S., Marino, G.: Mobile Agent Standards and Available Platforms. Computer Networks Journal, Special Issue on ’Mobile Agents in Intelligent Networks and Mobile Communication Systems’ 31(10) (1999)Perrone, P.J., Chaganti, K.: J2EE Developer’s Handbook. Sam’s Publishing, Indianapolis (2003)Apache ActiveMQ, http://activemq.apache.org/IBM WebSphere MQSeries, http://mqseries.net/Object Management Group, http://www.omg.org/RTI Data Distribution Service. RTI corp., http://www.rti.com/OpenSplice DDS. PrismTech Ltd., http://www.prismtech.comVogel, A., Kerherve, B., von Bochmann, G., Gecsei, J.: Distributed Multimedia and QoS: A Survey. IEEE Multimedia 2(2), 10–19 (1995)Crawley, E., Nair, R., Rajagopalan, B.: RFC 2386: A Framework for QoS-based Routing in the Internet. IETF Internet Draft, 1–37 (1998)Foundation for Intelligent Physical Agents. FIPA Quality of Service Ontology Specification. Doc: SC00094A (2002)Sun Microsystems, Inc. Java(TM) Message Service Specification Final Release 1.1 (2002)Object Management Group (OMG). The Common Object Request Broker Architecture and Specification. CORBA 2.4.2 (2001