Data as a Service (DaaS) offers an effective provisioning model able to exploit the advantages of cloud computing in terms of accessibility and scalability when data providers need to make their data available to diff...
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Data as a Service (DaaS) offers an effective provisioning model able to exploit the advantages of cloud computing in terms of accessibility and scalability when data providers need to make their data available to different data consumers. Nevertheless, in settings where data are generated at the edge and they need to be propagated (e.g., Industry 4.0, Smart Cities), DaaS model suffers of some limitations: data transfer from the edge to the cloud - and viceversa - could require a significant time and privacy issues could hamper the possibility to move the data. Goal of this article is to propose a DaaS model based on the Fog Computing paradigm, which combines the advantages of both cloud and edge computing. The proposed solution implements an adaptive multi-agent system where each agent autonomously manages the placement of data in the most convenient location considering the quality of service requirements of the user that it is serving. To guarantee the collaboration of the agents without imposing a centralized control, a reinforcement learning algorithm will be enacted to balance between the local optimum for the single data consumers and the satisfaction of the global requirements of all consumers.
Currently enterprises are organising themselves in 'new' structures, alternatively called enterprise networks, virtual enterprises, supply chains. We are interested in enterprise networks in which decision and...
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Currently enterprises are organising themselves in 'new' structures, alternatively called enterprise networks, virtual enterprises, supply chains. We are interested in enterprise networks in which decision and information systems are distributed. We are searching for a global performance while controlling the architecture with local bilaterally negotiated co-decisions. We propose an architecture based on multi-agent system and the associated protocols, described by statecharts, to ensure as much as possible a global coherence and the convergence of the decision process. We propose models and tools in order to validate our approach by simulation of the multi-agent system. We employ our model on a particular problem in which enterprises are searching complementary resources (stocks, production capacities, components and/or transport capacities) in order to deal with unexpected orders different from the planned forecasting. The simulation considers parameters of the architecture systems in order to define how many unexpected orders must be treated in parallel the goal is to find a good equilibrium between minimisation of answer delay and maximisation of efficiency.
This work aims at studying new opportunities held by Auto-ID technologies in the operation and logistic management. On the one hand, these new information technologies will speed up information flows, and on the other...
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This work aims at studying new opportunities held by Auto-ID technologies in the operation and logistic management. On the one hand, these new information technologies will speed up information flows, and on the other hand, doing the shop floor and the product flow more visible will allow reconsidering centralised decision making processes. In this paper, a quick presentation of the RFID technology is done, after what drawbacks of classical centralised control systems are pointed out. Then, we address a way to improve a classic kanban control system, by using kanban cards as an informational/decisional entity in order to enrich shop-floor information/decision. (C) 2009 Elsevier B.V. All rights reserved
In this paper, the communication direction problem of a two-sensor tandem binary decisionsystem is considered. Rigorous analysis shows that the performance of communication from the sensor with higher noise power to ...
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In this paper, the communication direction problem of a two-sensor tandem binary decisionsystem is considered. Rigorous analysis shows that the performance of communication from the sensor with higher noise power to the sensor with lower noise power is not always better than the performance of the reverse communication direction when the signal and sensor noises are both Gaussian. This result can be extended to a more general two-sensor tandem binary decisionsystem without the assumption of a specific data distribution. This seems somewhat counterintuitive but has significance for optimization design of sensor communication direction. Computer experiments support our analytic results and illustrate interesting information which requires need further study.
In a multi-node distributed decision system under some conditions there are few or none permitted information exchange between the nodes, this makes the information fusion and final decision difficult. However if we t...
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ISBN:
(纸本)0819444812
In a multi-node distributed decision system under some conditions there are few or none permitted information exchange between the nodes, this makes the information fusion and final decision difficult. However if we treat this distributedsystem as a multi-agent system, and each node acts as an agent, it has some other node's historical experiences or knowledge for resolving problems and stored in additional case bases, so it can uses case based reasoning (CBR) and transposition reasoning to obtain the possible viewpoints or decisions of other nodes and then makes information fusion by itself This approach may reduce the subjectivism which is the weakness of pure transposition reasoning.
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