443 research outputs found

    An approach to rollback recovery of collaborating mobile agents

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    Fault-tolerance is one of the main problems that must be resolved to improve the adoption of the agents' computing paradigm. In this paper, we analyse the execution model of agent platforms and the significance of the faults affecting their constituent components on the reliable execution of agent-based applications, in order to develop a pragmatic framework for agent systems fault-tolerance. The developed framework deploys a communication-pairs independent check pointing strategy to offer a low-cost, application-transparent model for reliable agent- based computing that covers all possible faults that might invalidate reliable agent execution, migration and communication and maintains the exactly-one execution property

    CIC : an integrated approach to checkpointing in mobile agent systems

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    Internet and Mobile Computing Lab (in Department of Computing)Refereed conference paper2006-2007 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe

    Coordinated collaboration for e-commerce based on the multiagent paradigm.

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    Lee Ting-on.Thesis (M.Phil.)--Chinese University of Hong Kong, 2000.Includes bibliographical references (leaves 116-121).Abstracts in English and Chinese.Acknowledgments --- p.iAbstract --- p.iiChapter 1 --- Introduction --- p.1Chapter 1.1 --- Roadmap to the Thesis --- p.5Chapter 2 --- Software Agents and Agent Frameworks --- p.7Chapter 2.1 --- Software Agent --- p.7Chapter 2.1.1 --- Advantages of Agent --- p.10Chapter 2.1.2 --- Roles of Agent --- p.11Chapter 2.2 --- Agent Frameworks --- p.13Chapter 2.3 --- Communication Services and Concepts --- p.15Chapter 2.3.1 --- Message Channel --- p.15Chapter 2.3.2 --- Remote Procedure Call --- p.16Chapter 2.3.3 --- Event Channel --- p.17Chapter 2.4 --- Component --- p.18Chapter 3 --- Related Work --- p.20Chapter 3.1 --- Collaboration Behaviors --- p.20Chapter 3.2 --- Direct Coordination --- p.22Chapter 3.3 --- Meeting-oriented Coordination --- p.23Chapter 3.4 --- Blackboard-based Coordination --- p.24Chapter 3.5 --- Linda-like Coordination --- p.25Chapter 3.6 --- Reactive Tuple Spaces --- p.26Chapter 4 --- Background and Foundations --- p.27Chapter 4.1 --- Choice of Technologies --- p.27Chapter 4.2 --- Jini Technology --- p.28Chapter 4.2.1 --- The Lookup Service --- p.29Chapter 4.2.2 --- Proxy --- p.31Chapter 4.3 --- JavaSpaces --- p.32Chapter 4.4 --- Grasshopper Architecture --- p.33Chapter 5 --- The CoDAC Framework --- p.36Chapter 5.1 --- Requirements for Enabling Collaboration --- p.37Chapter 5.1.1 --- Consistent Group Membership --- p.37Chapter 5.1.2 --- Atomic Commitment --- p.39Chapter 5.1.3 --- Uniform Reliable Multicast --- p.40Chapter 5.1.4 --- Fault Tolerance --- p.40Chapter 5.2 --- System Components --- p.41Chapter 5.2.1 --- Distributed Agent Adapter --- p.42Chapter 5.2.2 --- CollaborationCore --- p.44Chapter 5.3 --- System Infrastructure --- p.45Chapter 5.3.1 --- Agent --- p.45Chapter 5.3.2 --- Distributed Agent Manager --- p.46Chapter 5.3.3 --- Collaboration Manager --- p.46Chapter 5.3.4 --- Kernel --- p.46Chapter 5.4 --- Collaboration --- p.47Chapter 5.5.1 --- Global Collaboration --- p.48Chapter 5.5.2 --- Local Collaboration --- p.48Chapter 6 --- Collaboration Life Cycle --- p.50Chapter 6.1 --- Initialization --- p.50Chapter 6.2 --- Resouces Gathering --- p.53Chapter 6.3 --- Results Delivery --- p.54Chapter 7 --- Protocol Suite --- p.55Chapter 7.1 --- The Group Membership Protocol --- p.56Chapter 7.1.1 --- Join Protocol --- p.56Chapter 7.1.2 --- Leave Protocol --- p.57Chapter 7.1.3 --- Recovery Protocol --- p.59Chapter 7.1.4 --- Proof --- p.61Chapter 7.2 --- Atomic Commitment Protocol --- p.62Chapter 7.3 --- Uniform Reliable Multicast --- p.63Chapter Chapter 8 --- Implementation --- p.66Chapter 8.1 --- Interfaces and Classes --- p.66Chapter 8.1.1 --- The CoDACAdapterInterface --- p.66Chapter 8.1.2 --- The CoDACEventListener --- p.69Chapter 8.1.3 --- The DAAdapter --- p.71Chapter 8.1.4 --- The DAManager --- p.75Chapter 8.1.5 --- The CoDACInternalEventListener --- p.77Chapter 8.1.6 --- The CollaborationManager --- p.77Chapter 8.1.7 --- The CollaborationCore --- p.78Chapter 8.2 --- Messaging Mechanism --- p.79Chapter 8.3 --- Nested Transaction --- p.84Chapter 8.4 --- Fault Detection --- p.85Chapter 8.5 --- Atomic Commitment Protocol --- p.88Chapter 8.5.1 --- Message Flow --- p.89Chapter 8.5.2 --- Timeout Actions --- p.91Chapter Chapter 9 --- Example --- p.93Chapter 9.1 --- System Model --- p.93Chapter 9.2 --- Auction Lifecycle --- p.94Chapter 9.2.1 --- Initialization --- p.94Chapter 9.2.2 --- Resource Gathering --- p.98Chapter 9.2.3 --- Results Delivery --- p.100Chapter Chapter 10 --- Discussions --- p.104Chapter 10.1 --- Compatibility --- p.104Chapter 10.2 --- Hierarchical Group Infrastructure --- p.106Chapter 10.3 --- Flexibility --- p.107Chapter 10.4 --- Atomicity --- p.108Chapter 10.5 --- Fault Tolerance --- p.109Chapter Chapter 11 --- Conclusion and Future Work --- p.111Chapter 11.1 --- Conclusion --- p.111Chapter 11.2 --- Future Work --- p.112Chapter 11.2.1 --- Electronic Commerce --- p.112Chapter 11.2.2 --- Workflow Management --- p.114Bibliography --- p.116Publication List --- p.12

    Exception handling in distributed workflow systems using mobile agents

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    2005-2006 > Academic research: refereed > Refereed conference paperVersion of RecordPublishe

    Global Semantic Integrity Constraint Checking for a System of Databases

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    In today’s emerging information systems, it is natural to have data distributed across multiple sites. We define a System of Databases (SyDb) as a collection of autonomous and heterogeneous databases. R-SyDb (System of Relational Databases) is a restricted form of SyDb, referring to a collection of relational databases, which are independent. Similarly, X-SyDb (System of XML Databases) refers to a collection of XML databases. Global integrity constraints ensure integrity and consistency of data spanning multiple databases. In this dissertation, we present (i) Constraint Checker, a general framework of a mobile agent based approach for checking global constraints on R-SyDb, and (ii) XConstraint Checker, a general framework for checking global XML constraints on X-SyDb. Furthermore, we formalize multiple efficient algorithms for varying semantic integrity constraints involving both arithmetic and aggregate predicates. The algorithms take as input an update statement, list of all global semantic integrity constraints with arithmetic predicates or aggregate predicates and outputs sub-constraints to be executed on remote sites. The algorithms are efficient since (i) constraint check is carried out at compile time, i.e. before executing update statement; hence we save time and resources by avoiding rollbacks, and (ii) the implementation exploits parallelism. We have also implemented a prototype of systems and algorithms for both R-SyDb and X-SyDb. We also present performance evaluations of the system

    Using mobility and exception handling to achieve mobile agents that survive server crash failures

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    Mobile agent technology, when designed and used effectively, can minimize bandwidth consumption and autonomously provide a snapshot of the current context of a distributed system. Protecting mobile agents from server crashes is a challenging issue, since developers normally have no control over remote servers. Server crash failures can leave replicas, instable storage, unavailable for an unknown time period. Furthermore, few systems have considered the need for using a fault tolerant protocol among a group of collaborating mobile agents. This thesis uses exception handling to protect mobile agents from server crash failures. An exception model is proposed for mobile agents and two exception handler designs are investigated. The first exists at the server that created the mobile agent and uses a timeout mechanism. The second, the mobile shadow scheme, migrates with the mobile agent and operates at the previous server visited by the mobile agent. A case study application has been developed to compare the performance of the two exception handler designs. Performance results demonstrate that although the second design is slower it offers the smaller trip time when handling a server crash. Furthermore, no modification of the server environment is necessary. This thesis shows that the mobile shadow exception handling scheme reduces complexity for a group of mobile agents to survive server crashes. The scheme deploys a replica that monitors the server occupied by the master, at each stage of the itinerary. The replica exists at the previous server visited in the itinerary. Consequently, each group member is a single fault tolerant entity with respect to server crash failures. Other schemes introduce greater complexity and performance overheads since, for each stage of the itinerary, a group of replicas is sent to servers that offer an equivalent service. In addition, future research is established for fault tolerance in groups of collaborating mobile agents

    Decentralized Orchestration of Open Services- Achieving High Scalability and Reliability with Continuation-Passing Messaging

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    The papers of this thesis are not available in Munin. Paper I: Yu, W.,Haque, A. A. M. “Decentralised web- services orchestration with continuation-passing messaging”. Available in International Journal of Web and Grid Services 2011, 7(3):304–330. Paper II: Haque, A. A. M., Yu, W.: “Peer-to-peer orchestration of web mashups”. Available in International Journal of Adaptive, Resilient and Autonomic Systems 2014, 5(3):40-60. Paper V: Haque, A. A. M., Yu, W.: “Decentralized and reliable orchestration of open services”. In:Service Computation 2014. International Academy, Research and Industry Association (IARIA) 2014 ISBN 978-1-61208-337-7.An ever-increasing number of web applications are providing open services to a wide range of applications. Whilst traditional centralized approaches to services orchestration are successful for enterprise service-oriented systems, they are subject to serious limitations for orchestrating the wider range of open services. Dealing with these limitations calls for decentralized approaches. However, decentralized approaches are themselves faced with a number of challenges, including the possibility of loss of dynamic run-time states that are spread over the distributed environment. This thesis presents a fully decentralized approach to orchestration of open services. Our flow-aware dynamic replication scheme supports both exceptional handling, failure of orchestration agents and recovers from fail situations. During execution, open services are conducted by a network of orchestration agents which collectively orchestrate open services using continuation-passing messaging. Our performance study showed that decentralized orchestration improves the scalability and enhances the reliability of open services. Our orchestration approach has a clear performance advantage over traditional centralized orchestration as well as over the current practice of web mashups where application servers themselves conduct the execution of the composition of open web services. Finally, in our empirical study we presented the overhead of the replication approach for services orchestration

    Big SaaS: The Next Step Beyond Big Data

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    Software-as-a-Service (SaaS) is a model of cloud computing in which software functions are delivered to the users as services. The past few years have witnessed its global flourishing. In the foreseeable future, SaaS applications will integrate with the Internet of Things, Mobile Computing, Big Data, Wireless Sensor Networks, and many other computing and communication technologies to deliver customizable intelligent services to a vast population. This will give rise to an era of what we call Big SaaS systems of unprecedented complexity and scale. They will have huge numbers of tenants/users interrelated in complex ways. The code will be complex too and require Big Data but provide great value to the customer. With these benefits come great societal risks, however, and there are other drawbacks and challenges. For example, it is difficult to ensure the quality of data and metadata obtained from crowdsourcing and to maintain the integrity of conceptual model. Big SaaS applications will also need to evolve continuously. This paper will discuss how to address these challenges at all stages of the software lifecycle

    Exception handling in distributed workflow systems using mobile agents

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