A energy efficient multi-dimension model for system control in smart environment systems

A smart environment system should automatically control the devices according to the sensing information and users' requirements so as to keep the environmental elements (e.g., temperature, light) within the desired range. System control with minimum power is one key issue in such a system. In this paper, we propose a multi-dimension model for system control. In this model, each environmental element is abstracted into a dimension, such that a service with conditions and targets can be formulated as a multi-dimensional service space, and a smart environment with many services may map to a comprehensive multi-dimensional service space through space computation. Based on this model, we propose a minimum power adjustment algorithm for energy-efficient scheduling in smart environment, which transforms the optimal control problem into the problem of the shortest weighted distance of point-to-polygonal in multi-dimensional space. Theoretical analysis and experimental results show that the proposed model is effective and efficient in energy-efficient system control. It is important to point out that the proposed algorithms are scalable when the number of dimensions or services increases.