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Trust and uncertainty in distributed environments : application to the management of dataand data sources quality in M2M (Machine to Machine) systems.

Abstract : Trust and uncertainty are two important aspects of many distributed systems. For example, multiple sources of information can be available for the same type of information. This poses the problem to select the best source that can produce the most certain information and to resolve incoherence amongst the available information. Managing trust and uncertainty together forms a complex problem and through this thesis we develop a solution to this. Trust and uncertainty have an intrinsic relationship. Trust is primarily related to sources of information while uncertainty is a characteristic of the information itself. In the absence of trust and uncertainty measures, a system generally suffers from problems like incoherence and uncertainty. To improve on this, we hypothesize that the sources with higher trust levels will produce more certain information than those with lower trust values. We then use the trust measures of the information sources to quantify uncertainty in the information and thereby infer high level conclusions with greater certainty.A general trend in the modern distributed systems is to embed reasoning capabilities in the end devices to make them smart and autonomous. We model these end devices as agents of a Multi Agent System. Major sources of beliefs for such agents are external information sources that can possess varying trust levels. Moreover, the incoming information and beliefs are associated with a degree of uncertainty. Hence, the agents face two-fold problems of managing trust on sources and presence of uncertainty in the information. We illustrate this with three application domains: (i) The intelligent community, (ii) Smart city garbage collection, and (iii) FIWARE : a European project about the Future Internet that motivated the research on this topic. Our solution to the problem involves modelling the devices (or entities) of these domains as intelligent agents that comprise a trust management module, an inference engine and a belief revision system. We show that this set of components can help agents to manage trust on the other sources and quantify uncertainty in the information and then use this to infer more certain high level conclusions. We finally assess our approach using simulated and real data pertaining to the different application domains.
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Mondi Ravi. Trust and uncertainty in distributed environments : application to the management of dataand data sources quality in M2M (Machine to Machine) systems.. Other [cs.OH]. Université Grenoble Alpes, 2016. English. ⟨NNT : 2016GREAM090⟩. ⟨tel-01679344⟩

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