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Virtual Force and Glowworm Swarm Optimization Based Node Deployment Strategy for WSNs

机译:基于虚拟力和萤火虫群优化的无线传感器网络节点部署策略

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Wireless Sensor Networks (WSNs) can be viewed as a network with hundreds or thousands of randomly deployed sensors, whose coverage control problem has the characteristics of self-organized groups. This paper studies the coverage optimization strategy based on swarm intelligence for wireless sensor networks. In WSNs, the random deployment of nodes causes the coverage of the blind area and the redundancy of the coverage. We propose a new algorithm based on virtual force and glowworm swarm optimization algorithm. Firstly, the utilization rate of the nodes and the effective coverage of the network are the optimization objectives and the corresponding mathematical model is established. Then, the virtual force algorithm and the glowworm swarm optimization algorithm are used to solve the problem of modeling, and the optimal coverage scheme for WSNs is obtained. Simulation results show that the virtual force and glowworm swarm optimization algorithm can effectively improve the coverage of WSNs nodes, reduce the redundancy of sensor nodes, and reduce the cost of network effectively. Besides, the network survival time can get prolonged.
机译:无线传感器网络(WSN)可以被视为具有数百或数千个随机部署的传感器的网络,其覆盖控制问题具有自组织组的特征。本文研究了基于无线传感器网络的群体智能的覆盖优化策略。在WSN中,节点的随机部署导致盲区的覆盖范围和覆盖的冗余。我们提出了一种基于虚拟力和萤火虫群优化算法的新算法。首先,节点的利用率和网络的有效覆盖是优化目标,并且建立了相应的数学模型。然后,使用虚拟力算法和萤石群优化算法来解决建模的问题,获得用于WSN的最佳覆盖方案。仿真结果表明,虚拟力和萤石群优化算法可以有效地提高WSN节点的覆盖率,减少传感器节点的冗余,从而有效降低网络的成本。此外,网络生存时间可以长时间延长。

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