【摘要】 当前网络覆盖优化控制方法网络覆盖控制系数小、控制能耗高,提出基于粒子群的异构环境下高速互联网络覆盖优化控制方法。定义异构环境下高速互联网络目标区域,将其划分为若干个待监测区域,并在不影响网络覆盖优化控制的前提下进行建模前假设。在假设下对网络内处在工作下的传感器节点集合覆盖的网格点总数量和处在睡眠下的传感器数量进行计算,将两者结合得到异构环境下高速互联网络覆盖优化控制模型。以网络覆盖优化控制模型为目标函数,利用粒子群算法对目标函数进行求解。对粒子数量和粒子位置、速度进行初始化,将目标函数作为适应度函数,更新粒子飞行速度和位置。判断是否满足寻优结束条件,如果满足,则将目标函数最优解输出,完成异构环境下高速互联网络覆盖优化控制。实验结果表明,所提方法网络覆盖控制系数大,控制能耗低。上述方法具有较为优越的网络覆盖优化控制效果,可行性较强。更多还原

【Abstract】 At present, the network coverage optimization control method has small network coverage control coefficient and high control energy consumption. In this paper, we propose an optimization control method for high-speed internet coverage in heterogeneous environment based on particle swarm optimization. First of all, we defined the target area of high-speed internet in heterogeneous environment and divided it into some areas to be monitored, and then made assumptions before modeling without affecting network coverage optimization control. Based on the assumption, we calculated the total number of grid points covered by the set of sensor nodes under working state and the number of sensors under sleep, and then combined both of them to obtain the model of high-speed internet coverage optimization control in heterogeneous environment. Taking the network coverage optimization control model as the objective function, we used the particle swarm algorithm to solve the objective function. In addition, we initialized the number of particles, the position and velocity of particle. Taking the objective function as the fitness function, we updated the flight speed and position of particle. Finally, we judged whether it satisfied the end condition of optimization. If yes, we outputted the optimal solution of objective function. Thus, we finished the optimization control of high-speed internet in heterogeneous environment. Simulation results show that the proposed method has large network control coefficient and low energy consumption. Meanwhile, this method has better effect of network coverage optimization control and strong feasibility.更多还原