基于离散粒子群算法的无线传感器网络拓扑优化
2021-09-14黄红波王勇智
黄红波 王勇智



摘要:无线传感器网络技术的出现使得农业更加精准化、智能化,其在农业上的应用环境如果园与水果大棚等往往具有面积大、作物多等特点,需要更多的传感器节点以用于监测。由于传感器节点往往使用电池进行供电,有限的能量也给网络的鲁棒性带来了更大的挑战。基于离散粒子群算法设计了一种无线传感器网络的拓扑优化算法,在保证网络覆盖的情况下,通过尽可能减少活动节点的数量来降低网络的能量损耗,延长网络的生命周期,从而提高无线传感器网络的鲁棒性。
关键词:无线传感器网络;离散粒子群优化算法;网络拓扑
Abstract:The emergence of wireless sensor network technology makes agriculture more precise and intelligent. Its application environment in agriculture, such as gardens and fruit greenhouses, often has the characteristics of a large area and many crops, and more sensor nodes are needed for monitoring. Since batteries often power sensor nodes, limited energy brings more significant challenges to the network's robustness. This paper sets up a topology optimization algorithm for wireless sensor networks based on the discrete particle swarm algorithm. Under the condition of ensuring network coverage, the energy loss of the network is reduced by reducing the number of active nodes as much as possible, and the life cycle of the network is prolonged, thereby improving the robustness of the wireless sensor network.
Key words:wireless sensor network; discrete particle swarm optimization algorithm; network topology
1 引言
无线传感器网络的迅速发展,推动了农业的精准化、智能化发展。为最大化无线传感器网络的生命周期,保障农业环境监测的稳定性,研究降低网络能耗的方法至关重要[1,2]。粒子群算法(Particle Swarm Optimization, PSO)[3]模仿鸟群、鱼群等群体智能,将连续空间的优化求解问题转化为粒子朝着全局最优解不断移动的过程,其搜索速度快、效率高、算法简单,但对于离散的优化问题处理不佳[4]。为了解决在进行农业大棚环境监测过程中,无线传感器网络存在的各节点剩余能量及负载不均的问题,我们设计了一种基于离散粒子群算法的网络拓扑优化算法(DiscreteParticle Swarm OptimizationforTopologyControl, DPSOTC),算法采用一个激活函数将连续空间内的粒子位置转化为离散空间内的位置,通过将节点的邻居节点数以及剩余能量等建立适应度函数,来优化无线传感器网络的拓扑,能有效求出满足网络覆盖条件下所需的最少活动节点数,从而能提高无线传感器网络的生命周期,增强网络的鲁棒性。……
