EN-DADA: Node task assignment algorithm for energy harvesting wireless multimedia sensor networks

Today, a directional wireless multimedia sensor network is a popular environment for solving the task assignment problem. Achieving long-term frontal monitoring of moving objects is a crucial challenge for scholars in this field. Utilizing directional sensors equipped with energy harvesting is an effective technique to enhance network performance. In this way, the energy of nodes is no longer limited to batteries and can result in better frontal monitoring. In this method, each sensor categorizes tasks based on its own energy, allowing the determination of task execution nodes through bidding. The present study proposes a distributed algorithm for directional task assignment, EN-DADA, based on energy harvesting. The task was first classified to determine the candidate node set that could execute the task, and then the task assignment was determined according to the monitoring income of each node in the candidate node set. The comparative analysis confirmed that the proposed method had advantages in terms of task revenue and network lifetime when using the same energy harvesting model. A model of directed sensor nodes with solar energy harvesting is introduced in this paper, where the energy of such nodes is no longer limited to batteries and the directed sensing area enables better frontal tracking. On this basis, we propose a distributed algorithm for directional task assignment.image