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• W2420921617 abstract "Over the past 5 to 10 years, research is numerous on energy reduction in IT (mainly electricity reduction). Several studies indeed alerted the stakeholders and environmental agencies on the urgency of the problem of the energy consumption of large scale infrastructures, like data centres, clouds or simply companies running servers and lots of IT equipment. This awareness moved from a non-so-important issue to major constraints on the operation of these infrastructures. In some cases, the operational costs reach the investment costs, urging new methodologies to appear in order to reduce costs and ecological impact. As of today, new hardware are developed by equipment manufacturers to decrease these costs. Only few and basic techniques are offered at the software and middleware levels out-of-the-box: But in laboratories, some techniques have proven on synthetic data, dedicated workflows or selected applications, to be able to save energy during the lifetime of an infrastructure, in several contexts, from Cloud to HPC in particular. Unfortunately, the transfer (or even the knowledge of the existence) of these techniques to industries is limited to project partners, innovative companies or large private research centres, able to invest time (thus money) on this topic. In my thesis, I investigate the reasons restraining the large adoption of several research results, from the simpler ones to more elaborated ones and I model the ties and interactions between the actors of the technological transfer. The target field has been restricted to Green IT but the methodology and the developed models can be extended to other domains as well. The idea is to identify, on the scale of technical maturity for wider adoption, what is missing and how to increase the speed of the transfer of scientific knowledge. The methodology is based on the following path: First, identifying the actors involved in the process of technology transfer, and understanding their motivations, their means of actions and their limitations. After a study of the state of the art in the domain of innovation diffusion and innovation management, this phase involved the production and the analysis of a dedicated survey targeting researchers and companies, from different size and turnover, restricted to those working in the Green IT field. Identifying each actor is not sufficient since they all interact; therefore their links and the potential of these links for technology transfer have also been studied carefully in a second phase so as to identify the most important ones, with the same methodology with the actors' identification. From these two phases, a multi-agent system (MAS) has been designed." @default.
• W2420921617 created "2016-06-24" @default.
• W2420921617 creator A5074667439 @default.
• W2420921617 date "2015-11-26" @default.
• W2420921617 modified "2023-09-24" @default.
• W2420921617 title "Contribution to the modeling of technology transfer in green IT with multi-agent system" @default.
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