Energy Efficient Joint Data Aggregation and Link Scheduling in Solar Sensor Networks
Solar sensor nodes equipped with micro-solar subsystems provide a novel approach to harvest ambient energy, which partially alleviated the energy-limitation in traditional wireless sensor networks. However, it also poses new challenges that the amounts of energy harvested by nodes are dynamic and unbalanced among them thus network life cannot be necessarily prolonged if no well-designed energy-scheduling is adopted. Herein, the authors present an algorithm to construct Energy-efficient Data Aggregation Tree (EDAT) based on a Maximum-Weighted Connected Dominating Set (MaCDS). The EDAT aims to prolong network life by minimizing differences in energy consumption among sensor nodes.