10,047 research outputs found

    Event-B Patterns for Specifying Fault-Tolerance in Multi-Agent Interaction

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    Interaction in a multi-agent system is susceptible to failure. A rigorous development of a multi-agent system must include the treatment of fault-tolerance of agent interactions for the agents to be able to continue to function independently. Patterns can be used to capture fault-tolerance techniques. A set of modelling patterns is presented that specify fault-tolerance in Event-B specifications of multi-agent interactions. The purpose of these patterns is to capture common modelling structures for distributed agent interaction in a form that is re-usable on other related developments. The patterns have been applied to a case study of the contract net interaction protocol

    Towards security monitoring patterns

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    Runtime monitoring is performed during system execution to detect whether the system’s behaviour deviates from that described by requirements. To support this activity we have developed a monitoring framework that expresses the requirements to be monitored in event calculus – a formal temporal first order language. Following an investigation of how this framework could be used to monitor security requirements, in this paper we propose patterns for expressing three basic types of such requirements, namely confidentiality, integrity and availability. These patterns aim to ease the task of specifying confidentiality, integrity and availability requirements in monitorable forms by non-expert users. The paper illustrates the use of these patterns using examples of an industrial case study

    An Incremental Process for the Development of Multi-agent Systems in Event-B

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    A multi-agent system is a group of software or hardware agents that cooperate or compete to achieve individual or shared goals. A method for developing a multi-agent system must be capable of modelling the concepts that are central to multi-agent systems. These concepts are identified in a review of Agent Oriented Software Engineering methodologies. The rigorous development of complex systems using formal methods can reduce the number of design faults. Event-B is a formal method for modelling and reasoning about reactive and distributed systems. There is currently no method that guides the developer specifically in the modelling of agent-based concepts in Event-B. The use of formal methods is seen by some developers as inaccessible. This thesis presents an Incremental Development Process for the development of multi-agent systems in Event-B. Development following the Incremental Development Process begins with the construction of informal models, based on agent concepts. The informal models relate system goals using a set of relationships. The developer is provided with guidance to construct formal Event-B models based on the informal design. The concepts that are central to multi-agent systems are captured in the Event-B models through the translation from the goal models. The Event-B models are refined and decomposed into specifications of roles that will be performed by the agents of the system. Two case studies illustrate how the Incremental Development Process can be applied to multi-agent systems. An additional aid to the developer presented in this thesis is a set of modelling patterns that provide fault-tolerance for Event-B models of interacting agents

    A Lightweight and Flexible Mobile Agent Platform Tailored to Management Applications

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    Mobile Agents (MAs) represent a distributed computing technology that promises to address the scalability problems of centralized network management. A critical issue that will affect the wider adoption of MA paradigm in management applications is the development of MA Platforms (MAPs) expressly oriented to distributed management. However, most of available platforms impose considerable burden on network and system resources and also lack of essential functionality. In this paper, we discuss the design considerations and implementation details of a complete MAP research prototype that sufficiently addresses all the aforementioned issues. Our MAP has been implemented in Java and tailored for network and systems management applications.Comment: 7 pages, 5 figures; Proceedings of the 2006 Conference on Mobile Computing and Wireless Communications (MCWC'2006

    Step-wise development of resilient ambient campus scenarios

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    This paper puts forward a new approach to developing resilient ambient applications. In its core is a novel rigorous development method supported by a formal theory that enables us to produce a well-structured step-wise design and to ensure disciplined integration of error recovery measures into the resulting implementation. The development method, called AgentB, uses the idea of modelling database to support a coherent development of and reasoning about several model views, including the variable, event, role, agent and protocol views. This helps system developers in separating various modelling concerns and makes it easier for future tool developers to design a toolset supporting this development. Fault tolerance is systematically introduced during the development of various model views. The approach is demonstrated through the development of several application scenarios within an ambient campus case study conducted at Newcastle University (UK) as part of the FP6 RODIN project. © 2009 Springer Berlin Heidelberg

    AI Solutions for MDS: Artificial Intelligence Techniques for Misuse Detection and Localisation in Telecommunication Environments

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    This report considers the application of Articial Intelligence (AI) techniques to the problem of misuse detection and misuse localisation within telecommunications environments. A broad survey of techniques is provided, that covers inter alia rule based systems, model-based systems, case based reasoning, pattern matching, clustering and feature extraction, articial neural networks, genetic algorithms, arti cial immune systems, agent based systems, data mining and a variety of hybrid approaches. The report then considers the central issue of event correlation, that is at the heart of many misuse detection and localisation systems. The notion of being able to infer misuse by the correlation of individual temporally distributed events within a multiple data stream environment is explored, and a range of techniques, covering model based approaches, `programmed' AI and machine learning paradigms. It is found that, in general, correlation is best achieved via rule based approaches, but that these suffer from a number of drawbacks, such as the difculty of developing and maintaining an appropriate knowledge base, and the lack of ability to generalise from known misuses to new unseen misuses. Two distinct approaches are evident. One attempts to encode knowledge of known misuses, typically within rules, and use this to screen events. This approach cannot generally detect misuses for which it has not been programmed, i.e. it is prone to issuing false negatives. The other attempts to `learn' the features of event patterns that constitute normal behaviour, and, by observing patterns that do not match expected behaviour, detect when a misuse has occurred. This approach is prone to issuing false positives, i.e. inferring misuse from innocent patterns of behaviour that the system was not trained to recognise. Contemporary approaches are seen to favour hybridisation, often combining detection or localisation mechanisms for both abnormal and normal behaviour, the former to capture known cases of misuse, the latter to capture unknown cases. In some systems, these mechanisms even work together to update each other to increase detection rates and lower false positive rates. It is concluded that hybridisation offers the most promising future direction, but that a rule or state based component is likely to remain, being the most natural approach to the correlation of complex events. The challenge, then, is to mitigate the weaknesses of canonical programmed systems such that learning, generalisation and adaptation are more readily facilitated

    An incremental process for the development of multi-agent systems in Event-B

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    A multi-agent system is a group of software or hardware agents that cooperate or compete to achieve individual or shared goals. A method for developing a multi-agent system must be capable of modelling the concepts that are central to multi-agent systems. These concepts are identified in a review of Agent Oriented Software Engineering methodologies. The rigorous development of complex systems using formal methods can reduce the number of design faults. Event-B is a formal method for modelling and reasoning about reactive and distributed systems. There is currently no method that guides the developer specifically in the modelling of agent-based concepts in Event-B. The use of formal methods is seen by some developers as inaccessible. This thesis presents an Incremental Development Process for the development of multi-agent systems in Event-B. Development following the Incremental Development Process begins with the construction of informal models, based on agent concepts. The informal models relate system goals using a set of relationships. The developer is provided with guidance to construct formal Event-B models based on the informal design. The concepts that are central to multi-agent systems are captured in the Event-B models through the translation from the goal models. The Event-B models are refined and decomposed into specifications of roles that will be performed by the agents of the system. Two case studies illustrate how the Incremental Development Process can be applied to multi-agent systems. An additional aid to the developer presented in this thesis is a set of modelling patterns that provide fault-tolerance for Event-B models of interacting agents.EThOS - Electronic Theses Online ServiceGBUnited Kingdo
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