Energy-Efficient Design By Cross-Layer Optimization For Wireless Sensor Networks

Wireless sensor networks, which help people to interact with physical world, is application centric. Because system resource is limited, especially for the energy resource, it is a very important research issue to achieve minimum energy consumption . Thus, how to actualize energy-efficient data transmission becomes a key problem and hot topic.In recent years, there are already some research works on the energy cost for wireless sensor networks, and much literature brought forward different solution methods, however, these methods are limited in each layer of communication protocol. For example, we can reduce the consumption by avoiding the collision in the transmitting process through optimizing the MAC layer. But it may exchange the parameters of MAC layer while optimizing the network layer. In a word, it is not comprehensive to optimize a signal layer. So, it is necessary to explore energy efficient scheme by cross-layer to save the energy.In this thesis, we take two energy-efficient schemes by cross-layer optimization. On one hand, we establish an optimal schedule in MAC layer based on the sources of power consumption. Through the schedule, we can diminish the idle listen time and avoid the most confliction. Making the nodes closer to the base station to work randomly, we can average the working time of these nodes, so the energy cost could be averaged. This scheme could avoid the problem that some nodes use up its energy earlier. On the other hands, we take a cluster scheme for the nodes closer to the base station. We could select the working nodes by the residual energy. And according to the scheme, we are able to average the energy consumption. Through the two schemes, we could achieve the purpose of prolonging the lifetime of wireless sensor network.We evaluate the performance of the proposed schemes by simulation using the NS-2. From the simulation, we find that the performance is better than the single layered schemes whether in the network based on the working time or the working load when the random scheme or the cluster scheme is adopted. In other words, the effect using the cross-layer scheme we presented is more optimal than the layered scheme. And another simulation result shows that the total residual energy of all nods and the residual energy of each node when the cross-layer clustering scheme is adopted are all higher than them when the layered scheme is adopted.