Routing Algorithm Research On Energy Optimization For Wireless Sensor Networks

Routing algorithms help wireless sensor networks to complete the task and select the best path to transmit data packets. However, due to the limited energy of wireless sensor networks, the node is prone to delay in data transmission and cut down in life cycles.This thesis analyses the routing algorithm and clustering protocols energy optimization based on the domestic and foreign scholars on wireless sensor networks, proposes the ant colony algorithm and clustering routing protocol energy optimization. Finally, this thesis uses wireless injection attack to test and verify energy-optimization effect in TinyOS. The main content includes the following three aspects:(1) This thesis proposes an energy optimization algorithm(IACAEO) based on ant colony algorithm. This algorithm improves the next hop node selection probability and the pheromone update rule, focuses on comparing mode residual energy and distance between nodes and nodes, and adds weighting factor in the remaining energy and path’s pheromone. Simulation results show that this method can avoid the nodes excessive consumption on the path, and it is possible to reduce the overall consumption of wireless sensor networks.(2) This thesis proposes a fuzzy logic which is used the election of cluster head on wireless sensor networks, which use nodes residual energy and the total distance between two nodes in the range of a radius as two parameters to inference the election of cluster head. In order to avoid remote cluster head consume too much energy in terms of sending a message, so super cluster head is elected in all cluster heads which is responsible for remote cluster heads to forward packet. Simulation results show that the total energy consumption of wireless sensor networks is lower than LEACH and CHEF, and this method is conducive to the stability of wireless sensor networks.(3) This thesis verifies the energy optimization effect of two routing algorithms via the wireless injection attack. To evaluate the performance of the two algorithms proposed in this thesis, both of them are adopted in TinyOS and attacked via wireless injection. The results show that in terms of energy consumption IACAEO algorithm is lower than traditional ant colony algorithm, and FLCHEFP algorithm is much lower than LEACH and CHEF.