Scalable Energy-Aware Dynamic Task Allocation

Battery energy limitation is one of the main challenges in the mobile ad hoc networks. Several hardware and software based techniques have been proposed in this field. Energy aware task scheduling is one of the software methods where the scheduling policy aims at optimizing the energy. Most of the previous work have achieved significant energy savings for individual mobile nodes but did not consider overall network lifetime and scalability. In this paper, we propose a Scalable Energy Aware Dynamic Task Allocation technique (SEADTA) for prolonging the network lifetime. In our model, the network lifetime is divided into many rounds. At the beginning of each round a new energy aware clustering algorithm is executed in order to arrange the network nodes in a parent-child structure. Based on the proposed technique, selected parents are used in the remote allocation such that minimum residual energy is maximized at the end of each round. The results of our simulation showed that our proposed scheme makes a significant improvement in the network lifetime while simultaneously minimizing the energy consumption and time delay for each task