Research On Swarm Intelligence Based Routing Algorithm For WSN

Wireless sensor networks technology has become one of the hot research directions of modern technology. This study has important scientific significance and application prospects. The energy, bandwidth, computation, storage and communication of the sensors are so limited that the traditional wireless routing protocols are not suited for wireless sensor networks. Therefore design an energy-saving routing protocol for wireless sensor networks which support quality of service have great significance.The genetic algorithm has strong global search capability and parallelism, not easy to fall into local optimum, it is universal and depends on little application knowledge, and the genetic algorithm can be applet to both continuous space and continuous space. However, the genetic algorithm can not make use of enough system output information, it has to do a large redundancy repeat for the result when solving to certain scope, so the efficiency to solve precision results is reduced and a lot of energy is wasted. The ant algorithm converges on the optimization path through information pheromone accumulation and renewal, it has the ability of parallel processing and global searching and high robustness. In addition, the ant colony algorithm is easy to combine with other optimization methods. It is very suitable for network routing optimization problem. But the speed at which the ant algorithm gives the solution is slow, because there is little information pheromone on the path early, it is only suitable for the optimal solution but not suitable for a combination of optimization problems in continuous space. but the genetic algorithm applies to both continuous space and continuous space. Therefore, this paper proposes the idea of integration of genetic-ant algorithm to learn the advantages of the two algorithms, and improve the efficient of searching capability for wireless sensor networks. First, it adopts genetic algorithm to give information pheromone to distribute. Second, it makes use of the ant algorithm to give the precision of the solution.In the genetic algorithm, the length of the chromosome is not fixed; the crossover and mutation rules are improved. The conditions of the end of the genetic algorithm can control the start timing of the ant colony algorithm. In the ant colony algorithm, only increase the pheromone on the optimal path to accelerate the convergence speed, and it have joined the energy parameters in the ants select the probability function and fitness function, so the path is energy balance and good quality of service.The simulation results show that the proposed algorithm is a fast, real-time, safe and energy dominant routing algorithms. It can provide good quality of service and can be applied to the application of QoS requirements. Compared with the basic ant colony algorithm, the algorithm is more quickly and is lower energy consumption. So it is better adapt to the wireless sensor networks.