Thesis Summary:

This thesis, presented as a set of research papers, studies the problem of energy consumption growth in two spheres: Grid-Computing and Smart Environments. These problems are tackled through the establishment of energy-saving policies developed for each environment in order to save the maximum energy as possible.

In the Grid-Computing environment, seven energy-policies were designed in an attemp to minimize energy consumption through shutting resources down and booting them. These energy policies were tested by applying usage data from French Grid'5000 infrastructure and a simulation software tool developed specifically for this purpose. In general, it is proven that around 30\% of energy can be saved. The software tool, called Grid'5000 Toolbox, can simulate the behaviour of a Grid-Computing environment, whilst applying several energy policies, and can compute statistics such as energy consumption, usage, and the states of resources and can generate dynamic graphical representation of the state of the jobs deployed and that of the resources.

In Smart Environments where sensors perceive lighting conditions, the energy-saving policy adjusts lighting in order to satisfy user preferences and prevents energy from being wasted. A set of wireless sensors were deployed on two offices at the department of Computer Languages and Systems. This set of sensors is comprised of a mesh network through which the sensors interact in order to retrieve information about lighting, and air conditioning, whereby this information is sent to a central node. The dataset created over several months was employed to extract information about user lighting preferences, from the application of which it is proven that around 70\% of energy can be saved in lighting appliances.