Cloud computing enables scalable and flexible resource allocation. However, it often leads to unnecessary energy consumption due to inefficient user behaviors and resource provisioning strategies. This research explores sufficiency techniques in cloud environments and aims to reduce energy waste by encouraging both cloud users and providers to adopt more conscious resource usage practices.

We propose that simple user-driven optimizations can lead to significant energy reductions. To find the possible optimization techniques, we analyze job records from the Grid'5000 testbed. We investigate resource usage both during idle times and under utilization, and measure their impact on energy consumption. User behavior improvements could include selecting appropriate resources for workloads and actively managing idle periods. Our contribution focus on understanding resource usage patterns and ensuring that only the required resources are allocated.

To demonstrate how small adjustments in user practices can contribute to sustainability in cloud computing, we simulate these behavior changes and assess their impact on the overall idle consumption of the system. Using the simulation platform Batsim, we evaluate the potential energy savings when users adjust their behaviors. To achieve this, we perform simulations with original and modified workloads, and compare the results.

This study aims to bridge the gap between energy-efficient cloud management and user awareness. We believe that intentional sufficiency techniques rather than just technological advancements can drive substantial reductions in cloud energy consumption.