蚁群优化算法在WSN路由中的应用研究

介绍了基本蚁群算法的原理和适用范围,总结出了基本蚁群算法在求解最优路径问题时,虽然具有很强的发现较优解的能力,但是存在容易陷入局部最优解和收敛时间过长等问题。考虑到基本蚁群算法在无线传感器网络路由上应用的不足,提出了一种改进后的蚁群算法,并将其应用到传感器网络路由中。该算法不仅在状态转移概率公式中引入罚函数和动态权重因子,而且采用局部信息素更新和全局信息素更新结合的方式更新路径信息,充分考虑到传感器节点与节点间的传输距离,并且充分考虑传感器节点的剩余能量。最后通过仿真实验,得到了基本蚁群算法和改进后的蚁群算法在传感器节点剩余能量和传输数据包时网络延迟的不同曲线,验证了改进后的蚁群算法在无线传感器网络路由选择上的高效性。

Application study of ant colony optimization in wirelesssensor network routing

Though the basic ant colony algorithm can find out the optimum solution when solving optimal path problems,it is easy to fall into a local optimal solution，and meanwhile the convergence time is too long.Considering the lack of applications of the basic ant colony algorithm in wireless sensor network routing，we propose an improved ant colony algorithm，and apply it to the wireless sensor network routing. This algorithm not only adds the dynamic penalty function and the weighting factors to the state transition probability formula，but also combines the local pheromone update and the global pheromone update to update the path information.We fully take into account of the transmission distance from nodes to nodes and the residual energy of the sensor nodes as well.The simulation results obtain some different curves from the basic ant colony algorithm and the improved algorithm in the residual energy of the sensor nodes and network transmission delay in wireless sensor network routing，verifying the efficiency of the improved ant algorithm in wireless sensor network routing.