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作 者:田祥宏[1] Tian Xianghong(School of Computer Engineering, Jinling Institute of Technology, Nanjing 211169, China)
机构地区:[1]金陵科技学院计算机工程学院,江苏南京211169
出 处:《南京理工大学学报》2016年第5期566-572,580,共8页Journal of Nanjing University of Science and Technology
基 金:国家自然科学基金(60874091);江苏省自然科学基金(BK20130096)
摘 要:水下传感器网络的节点部署优化能够提高整个网络的覆盖度和均匀度。该文针对水下环境复杂时现有部署优化算法的局限性,提出了一种基于黏性流体算法的水下传感器网络节点部署优化方案。该算法以覆盖度为目标函数,将节点的部署过程模型化为流体流动的自然行为,并在方案中加入鱼群优化算法,进一步优化部署策略。仿真结果表明,融合智能鱼群算法的黏性流体部署方案可有效提高网络覆盖度和均匀度,优化网络性能。The optimization of the node deployment can improve the coverage and the uniformity for underwater sensor networks. In view of shortages of the existing optimization algorithms underwater the complex environment,a new optimizing node deployment scheme for underwater sensor networks is proposed based on the viscous fluid algorithm. By this scheme,the node deployment process is modeled as the natural behavior of fluid flow and the coverage is used as the object function. Then the fish swarm optimization algorithm is adopted to optimize the deployment strategy. The simulation results show that the scheme can effectively improve the coverage and the uniformity of network and optimize the network performance.
分 类 号:TP393[自动化与计算机技术—计算机应用技术]
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