There exist two classical and well-understood approaches to video-processing tasks (such as mixing or trans-coding) for videoconferencing. The first one is using a centralized multipoint control unit (MCU), hardware- or software-based, deployed on-premises or in the cloud. In the second approach, the video-processing tasks are directly handled in endpoints (i.e., equipment such as PCs, laptops, and tablets that are involved in the video session). Performance is then restricted by device characteristics, especially in the case of mobile devices. In this paper, we propose a third alternative approach. It has been shown that there exist significant computational resources in user equipment deployed in enterprises, which are under-utilized most of the time. In this paper, we propose a system, which distributes real-time video-processing tasks on these available resources. A dedicated multi-attribute decision-making (MADM) method is designed in order to take into account the variety of attributes impacting Quality of Experience. We enumerate a comprehensive list of events, which may cause distribution or redistribution of video-processing activities and provide simple algorithms to tackle all these cases. We then test the MADM algorithm by means of simulations in order to study the impact of the main critical parameters.