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              無人機使能的無線傳感網總能耗優化方法

              李敏 包富瑜 王恒

              李敏, 包富瑜, 王恒. 無人機使能的無線傳感網總能耗優化方法. 自動化學報, xxxx, xx(x): x?xx doi: 10.16383/j.aas.c220914
              引用本文: 李敏, 包富瑜, 王恒. 無人機使能的無線傳感網總能耗優化方法. 自動化學報, xxxx, xx(x): x?xx doi: 10.16383/j.aas.c220914
              Li Min, Bao Fu-Yu, Wang Heng. Optimization of total energy consumption for unmanned aerial vehicle-enabled wireless sensor networks. Acta Automatica Sinica, xxxx, xx(x): x?xx doi: 10.16383/j.aas.c220914
              Citation: Li Min, Bao Fu-Yu, Wang Heng. Optimization of total energy consumption for unmanned aerial vehicle-enabled wireless sensor networks. Acta Automatica Sinica, xxxx, xx(x): x?xx doi: 10.16383/j.aas.c220914

              無人機使能的無線傳感網總能耗優化方法

              doi: 10.16383/j.aas.c220914
              基金項目: 國家自然科學基金 (92267106, 61972061), 重慶英才計劃基礎研究與前沿探索項目 (cstc2021ycjh-bgzxm0017) 資助
              詳細信息
                作者簡介:

                李敏:重慶郵電大學自動化學院教授. 2014年獲得重慶大學博士學位. 主要研究方向為無線傳感器網絡, 無人機和無線功率傳輸. 本文通信作者. E-mail: limin@cqupt.edu.cn

                包富瑜:重慶郵電大學自動化學院碩士研究生. 主要研究方向為無線傳感器網絡和無人機. E-mail: baofuyu1218@163.com

                王恒:重慶郵電大學自動化學院教授. 2010年獲得重慶大學博士學位. 主要研究方向為工業物聯網, 無線傳感器網絡和時間同步. E-mail: wangheng@cqupt.edu.cn

              Optimization of Total Energy Consumption for Unmanned Aerial Vehicle-enabled Wireless Sensor Networks

              Funds: Supported by National Natural Science Foundation of China (92267106, 61972061) and Fundamental Research and Frontier Exploration Program of Chongqing, China (cstc2021ycjh-bgzxm0017)
              More Information
                Author Bio:

                LI Min Professor at the College of Automation, Chongqing University of Posts and Telecommunications. She received her Ph. D. degree from Chongqing University in 2014. Her research interest covers wireless sensor networks, unmanned aerial vehicle, and wireless power transfer. Corresponding author of this paper

                BAO Fu-Yu Master student at the College of Automation, Chongqing University of Posts and Telecommunications. His research interest covers wireless sensor networks and unmanned aerial vehicle

                WANG Heng Professor at the College of Automation, Chongqing University of Posts and Telecommunications. He received his Ph. D. degree from Chongqing University in 2010. His research interest covers industrial internet of things, wireless sensor networks, and clock synchronization

              • 摘要: 為降低無人機(Unmanned aerial vehicle, UAV)使能的無線傳感網的能量消耗, 延長網絡生命周期, 該文提出一種在地面節點能量預算下系統總能耗優化方法. 首先, 提出地面節點聚類方法, 利用目標函數確定最優簇數, 改進模糊C均值算法構建能量均衡的集群, 采用退避定時器機制根據隸屬度和能量值選擇各集群的最優簇頭, 減少地面節點的能耗. 其次, 根據已選簇頭位置, 利用遺傳算法規劃UAV的飛行軌跡, 減小UAV能耗. 最后, 通過單純形搜索算法和連續凸逼近算法聯合優化簇頭發射功率和UAV懸停位置, 減小數據采集時系統的總能耗. 仿真結果表明, 所提方法優于所比較的方案.
              • 圖  1  系統模型

                Fig.  1  System model

                圖  2  不同簇頭數量下系統總能耗

                Fig.  2  Total energy consumption of the system with different numbers of cluster head

                圖  3  集群規模變化

                Fig.  3  Variation in size of clusters

                圖  4  集群內距離成本

                Fig.  4  Cost of the intra-cluster distance

                圖  5  節點存活數

                Fig.  5  The number of alive nodes

                圖  6  網絡剩余能量

                Fig.  6  Residual energy of network

                圖  7  系統能量消耗

                Fig.  7  System energy consumption

                圖  8  UAV飛行軌跡

                Fig.  8  UAV flight trajectory

                圖  9  不同簇成員個數對系統能耗的影響

                Fig.  9  Effect of different number of cluster members on system energy consumption

                圖  10  不同簇頭能量預算對系統能耗的影響

                Fig.  10  Impact of different cluster head energy budgets on system energy consumption

                表  1  仿真參數

                Table  1  Simulation parameter

                參數符號參數值參數符號參數值
                $\alpha$0.03${{v}_{v}}$10 m/s
                $\beta$10${{E}_{cap}}$50 J
                $\eta LoS$3 dB$l$1 Mb
                $\eta NLoS$13 dB${{\alpha }_{1}}$,${{\alpha }_{2}}$0.5
                ${{d}_{0}}$1 m$\phi $1 000
                ${{\sigma }^{2}}$?174 dBm/Hz${{v}_{u}}$15 m/s
                下載: 導出CSV

                表  2  不同算法的VSC比較

                Table  2  VSC comparison of different algorithms

                實驗次數OCM-FCM算法IEECP算法SHM-FCM算法
                1428.4052.8548.50
                2362.3549.0546.70
                3271.1566.5557.65
                4254.2051.7543.45
                5272.4058.6550.50
                6387.5052.9031.75
                7329.1549.3543.54
                8289.4558.4562.55
                9290.2555.8055.20
                10319.1546.7537.50
                下載: 導出CSV

                表  3  網絡穩定性比較

                Table  3  Comparison of network stability

                聚類算法FNDHNDLNDWFND
                OCM-FCM1751540.0065
                IEECP21042260.0089
                SHM-FCM91764160.0220
                下載: 導出CSV
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                        • 收稿日期:  2022-11-24
                        • 錄用日期:  2023-04-04
                        • 網絡出版日期:  2023-04-28

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