基于改进MPA的分层无线传感器网络优化部署

分层的无线传感器网络中,汇聚层节点的部署位置,对感知层节点的发射功率起到决定性影响。因此,本文对3D环境下的分层无线传感器网络的优化部署进行研究。以感知层节点与汇聚层节点的全连接以及感知层节点发射功率的平衡为前提,对汇聚层节点的部署位置和感知层节点的发射功率进行联合优化。为了求解上述优化问题,本文提出了一种结合Tent混沌序列的海洋捕食者(MPA)改进算法:TMPA。多个测试函数的数值计算结果表明,TMPA比MPA具有更好的收敛性能。在此基础上,本文提出了一种基于TMPA的分层无线传感器网络的优化部署机制。仿真结果表明,本文的优化部署机制能够在保证感知层节点全连接的前提下,极大地降低并平衡感知层节点的能耗,从而延长了网络的寿命。

Optimized Deployment of Hierarchical Wireless Sensor Networks Based on Improved MPA

In hierarchical wireless sensor networks(WSNs),the deployment of convergence nodes plays a decisive role in the transmit power of sensing nodes.Therefore,this paper studies the optimal deployment of hierarchical WSNs in 3 D environments where the deployment locations of convergence nodes and transmit powers of sensing nodes are jointly optimized on the premise of full connection between sensing nodes and convergence nodes and the balance of transmit powers of sensing nodes.In order to solve the above optimization problem,an improved marine predator algorithm(MPA),named tent marine predator algorithm(TMPA),is proposed in this paper.The numerical results of several benchmark functions show that TMPA has better convergence performance than the canonical MPA.Then,this paper proposes a TMPA based hierarchical WSN deployment mechanism.The simulation results show that the optimized deployment mechanism can greatly reduce and balance the energy consumption of the sensing nodes under the premise of ensuring the full connection of the sensing nodes,thus prolonging the network lifetime.