2.793

                    2018影響因子

                    (CJCR)

                    • 中文核心
                    • EI
                    • 中國科技核心
                    • Scopus
                    • CSCD
                    • 英國科學文摘

                    留言板

                    尊敬的讀者、作者、審稿人, 關于本刊的投稿、審稿、編輯和出版的任何問題, 您可以本頁添加留言。我們將盡快給您答復。謝謝您的支持!

                    姓名
                    郵箱
                    手機號碼
                    標題
                    留言內容
                    驗證碼

                    基于旋翼無人機近地面空間應急物聯網節點動態協同部署

                    王巍 彭力 趙繼軍 朱天宇 崔益豪 田立勤

                    王巍, 彭力, 趙繼軍, 朱天宇, 崔益豪, 田立勤. 基于旋翼無人機近地面空間應急物聯網節點動態協同部署. 自動化學報, 2021, 47 (8): 2002?2015 doi: 10.16383/j.aas.c180146
                    引用本文: 王巍, 彭力, 趙繼軍, 朱天宇, 崔益豪, 田立勤. 基于旋翼無人機近地面空間應急物聯網節點動態協同部署. 自動化學報, 2021, 47 (8): 2002?2015 doi: 10.16383/j.aas.c180146
                    Wang Wei, Peng Li, Zhao Ji-Jun, Zhu Tian-Yu, Cui Yi-Hao, Tian Li-Qin. Dynamic cooperative deployment of emergency internet of things near ground space based on drone. Acta Automatica Sinica, 2021, 47 (8): 2002?2015 doi: 10.16383/j.aas.c180146
                    Citation: Wang Wei, Peng Li, Zhao Ji-Jun, Zhu Tian-Yu, Cui Yi-Hao, Tian Li-Qin. Dynamic cooperative deployment of emergency internet of things near ground space based on drone. Acta Automatica Sinica, 2021, 47 (8): 2002?2015 doi: 10.16383/j.aas.c180146

                    基于旋翼無人機近地面空間應急物聯網節點動態協同部署

                    doi: 10.16383/j.aas.c180146
                    基金項目: 

                    國家重點研發計劃 2018YFF0301004

                    國家重點研發計劃 2018YFD0400902

                    國家自然科學基金 61802107

                    國家自然科學基金 61873112

                    教育部–中國移動科研基金 MCM20170204

                    河北省自然科學基金 F2015402108

                    河北省物聯網數據采集與處理工程技術研究中心開放課題 2016-2

                    江蘇省博士后科研資助計劃項目 1601085C

                    詳細信息
                      作者簡介:

                      彭力 ?? 江南大學教授. 2002年獲得北京科技大學控制理論與控制工程博士學位. 主要研究方向為視覺物聯網.E-mail: pengli@jiangnan.edu.cn

                      趙繼軍 ?? 河北工程大學教授. 2003年獲得北京郵電大學電磁場與微波技術博士學位. 主要研究方向為寬帶通信網, 傳感網與物聯網.E-mail: zjijun@hebeu.edu.cn

                      朱天宇?? 河北工程大學信息與電氣工程學院碩士研究生.主要研究方向為無人機, SLAM.E-mail: zihan126410@sina.com

                      崔益豪?? 河北工程大學信息與電氣工程學院碩士研究生.主要研究方向為物聯網監測系統.E-mail: yihaocui1994@163.com

                      田立勤?? 華北科技學院教授. 2009年獲得北京科技大學計算機應用技術博士學位.主要研究方向為物聯網遠程信息監控、網絡用戶行為認證.E-mail: tianliqin@ncist.edu.cn

                      通訊作者:

                      王巍    河北工程大學副教授. 2012年獲得北京科技大學信息工程學院控制科學與工程博士學位. 主要研究方向為公共安全物聯網, 隱式人機交互. 本文通信作者.E-mail: wangwei83@hebeu.edu.cn

                    • 本文責任編委 陳積明

                    Dynamic Cooperative Deployment of Emergency Internet of Things Near Ground Space Based on Drone

                    Funds: 

                    National Key Research and Development Program of China 2018YFF0301004

                    National Key Research and Development Program of China 2018YFD0400902

                    National Natural Science Foundation of China 61802107

                    National Natural Science Foundation of China 61873112

                    Education Ministry and China Mobile Science Research Foundation MCM20170204

                    Natural Science Foundation of Hebei Province of China F2015402108

                    Foundation of Internet of Things Data Acquisition and Processing Engineering Technology Research Center in Hebei Province 2016-2

                    Jiangsu Planned Projects for Postdoctoral Research Funds 1601085C

                    More Information
                      Author Bio:

                      PENG Li ?? Professor at Jiangnan University. He received his Ph. D. degree from University of Science & Technology Beijing in 2002. His main research is visual internet of things

                      ZHAO Ji-Jun ?? Professor at Hebei University of Engineering. He received his Ph. D. degreer from Beijing University of Posts and Telecommunications in 2003. His research interest covers broadband communication network, sensor network and internet of things

                      ZHU Tian-Yu?? Master student at School of Information & Electrical Engineering, Hebei University of Engineering. His research interest covers UAV and SLAM

                      CUI Yi-Hao?? Master student at School of Information & Electrical Engineering, Hebei University of Engineering. His main research is monitoring system of internet of things

                      TIAN Li-Qin?? Professor at North China Institute of Science and Technology. He received his Doctor degree from University of Science & Technology Beijing in 2009. His research interest covers remote monitoring of Internet of Things, network user behavior authentication

                      Corresponding author: WANG Wei    Associate professor at Hebei University of Engineering. He received his Ph. D. degree from University of Science & Technology Beijing in 2012. His research interest covers public safety internet of things and implicit human-computer interaction. Corresponding author of this paper
                    • Recommended by Associate Editor CHEN Ji-Ming
                    • 摘要: 針對基于旋翼無人機的近地面空間應急物聯網在缺少地面基站和能量受限的情況下, 可靠節能地遠距離傳輸重點區域全信息的要求, 研究由無人機組成的移動Ad-Hoc網絡的遠距離通信問題, 提出近地面空間應急物聯網空地節點動態協同部署方法. 首先, 對該類物聯網進行系統建模; 其次, 根據所建模型中無人機編隊大范圍、隊列化、微漂移地分散于監測區域的特點和編隊的聯合分布情況, 在提供可靠通信的同時, 將系統通信能耗和移動能耗的計算構建成二次約束二次規劃問題; 再次, 根據Gerschgorin圓盤定理和根的存在性定理, 證明了此問題為凸優化問題, 進而可求解得到移動地面站的最佳路徑點, 實現近地面空間應急物聯網空地節點動態協同部署. 最后, 通過實驗, 從通信耗能和運動耗能兩方面驗證了本文所提方法的有效性, 同時, 也分析了影響本文所述方法效能的因素.
                      Recommended by Associate Editor CHEN Ji-Ming
                      1)  本文責任編委 陳積明
                    • 圖  1  系統模型

                      Fig.  1  System model

                      圖  2  位置關系

                      Fig.  2  Position relationship

                      圖  3  Drones cube中無人機空基監測平臺立體結構

                      Fig.  3  The three-dimensional structure of the air based monitoring platform for unmanned aerial vehicle in drones cube

                      圖  4  不同分布的最佳路徑點$(h_{\text{min}} = 160 \text{m})$

                      Fig.  4  The optimal path points in different distribution condition $(h_{\text{min}} = 160 \text{m})$

                      圖  5  三種Drones cube分布下的MES移動距離

                      Fig.  5  MES moving distance under three kinds of drones cube distribution

                      圖  6  不同分布的Drones cube靜態通信能量$(H = 160 \text{m})$

                      Fig.  6  Static communication energy under different kinds of Drones cube distribution $(H = 160 \text{m})$

                      圖  7  直線分布Drones cube靜態通信能耗縱向不均衡率

                      Fig.  7  Vertical disequilibrium rate of energy consumption in Drones cube static communication under linear distribution

                      圖  8  三種Drones cube分布下的靜態通信能耗增長率

                      Fig.  8  Energy consumption growth rate of static communication under three kinds of Drones cube distribution

                      圖  9  直線分布的Drones cube靜態通信能耗與HD的關系

                      Fig.  9  The relationship between the energy consumption of drones cube static communication and H and D

                      圖  10  直線分布的Drones cube靜態通信能耗擬合

                      Fig.  10  Energy consumption fitting of drones cube static communication under linear distribution

                      圖  11  直線分布的Drones cube動態通信能耗$(H = 150, D = 75)$

                      Fig.  11  Dynamic communication energy consumption of drones cube under linear distribution$(H = 150, D = 75)$

                      表  1  國內外相關研究

                      Table  1  Related works

                      文獻 內容 網絡類型 無人機數量 不足
                      [4] 無人機最優部署與移動 D2D通信網絡 一個 未研究上行通信
                      [5] 無人機最優軌跡 Ad-hoc網絡 多個 未研究無人機運動
                      [6] 靜態地面用戶與無人機聯合最優部署 IoT (Internet of things) 多個 未研究地面用戶的動態問題
                      [7] 高效地數據采集與簇頭充電方法 WSN (Wireless sensor networks) 多個 只針對靜態傳感網, 未研究最優部署問題
                      [8-9] 節能的上行傳輸策略 IoT M2M (Machine-to machine)網絡 未考慮設備的運動
                      [10-11] 過載和中斷預防方法 蜂窩網絡 多個 未研究無人機覆蓋性能
                      [12] 無人機最優軌跡 WSN 多個 只針對靜態傳感設備
                      [13-14] 蜂窩網與D2D (Device-to-device)設備共存 蜂窩網絡 一個 未研究無人機的覆蓋和通信性能
                      下載: 導出CSV

                      表  2  仿真參數

                      Table  2  Simulation parameters

                      參數 描述
                      $f_{c}$ 載波頻率 $\text{2 GHz}$
                      $v_{\cdot}^{t}$ 地面移動中繼的速度 $\text{3.6 km/h}$
                      $E$ 各簇旋翼無人機用于通信總能量 $\text{3 J}$
                      $\delta$ 誤碼率要求 $10^{-8}$
                      $\varepsilon$ 視距通信概率要求 0.95
                      $N_{\text{o}}$ 噪聲功率譜密度 $-170$ dBm/Hz
                      $R_{\text}$ 數據傳輸速率 $\text{200 kbps}$
                      $B$ 傳輸帶寬 $\text{200 kHz}$
                      $\eta$ 附加路徑損耗 $\text{5 dB}$
                      $\psi$ 環境參數1 11.95
                      $\beta$ 環境參數2 0.14
                      下載: 導出CSV

                      表  3  旋翼無人機數量與算法運行時長

                      Table  3  Number of drones and algorithm running 09:39:56

                      分布形式 數量$K$ 算法運行時長$(\text{s})$ 平均時長$(\text{s})$
                      第1次 第2次 第3次 第4次 第5次
                      直線 96 10.773 10.722 10.683 10.731 10.689 10.719
                      108 10.788 10.753 10.761 10.742 10.814 10.772
                      120 10.795 10.821 10.728 10.801 10.722 10.773
                      三角 96 10.821 10.791 10.844 10.861 10.742 10.811
                      108 10.994 11.069 10.711 10.670 10.781 10.845
                      120 10.892 10.931 10.897 10.911 10.821 10.890
                      圓形 96 10.873 10.810 10.822 10.789 10.867 10.832
                      108 10.849 10.872 10.893 10.812 10.827 10.851
                      120 10.974 10.912 10.812 10.832 10.844 10.874
                      下載: 導出CSV

                      表  4  Drones cube簇數與算法運行時長

                      Table  4  Number of drones cube and algorithm running 09:42:00

                      分布形式 簇數$L$ 算法運行時長$(\text{s})$ 平均時長$(\text{s})$
                      第1次 第2次 第3次 第4次 第5次
                      直線 3 10.644 10.685 10.673 10.731 10.508 10.648
                      4 10.788 10.753 10.761 10.742 10.814 10.772
                      5 10.821 10.876 10.824 10.897 10.933 10.870
                      三角 3 10.878 10.787 10.709 10.801 10.822 10.799
                      4 10.994 11.069 10.711 10.670 10.781 10.845
                      5 10.892 10.977 11.021 10.709 10.898 10.899
                      圓形 3 10.842 10.801 10.756 10.722 10.793 10.782
                      4 10.849 10.872 10.893 10.812 10.827 10.851
                      5 10.910 10.953 10.871 11.213 10.945 10.978
                      下載: 導出CSV
                      360彩票
                    • [1] Mozaffari M, Saad W, Bennis M, et al. Mobile internet of things: can UAVs provide an energy-efficient mobile architecture. In: Proceeding of the 2016 IEEE Global Communications Conference (GLOBECOM). Piscataway, USA: IEEE, 2016. 1-6
                      [2] Sánchez-García J, García-Campos J M, Arzamendia M, et al. A survey on unmanned aerial and aquatic vehicle multi-hop networks: Wireless communications, evaluation tools and applications. Computer Communications, 2018, 119: 43-65 http://www.sciencedirect.com/science/article/pii/S0140366416304315
                      [3] Jawhar I, Mohamed N, Al-Jaroodi J, et al. Communication and networking of UAV-based systems: Classification and associated architectures. Journal of Network and Computer Applications, 2017, 84: 93-108 doi: 10.1016/j.jnca.2017.02.008
                      [4] Mozaffari M, Saad W, Bennis M, and et al. Unmanned aerial vehicle with underlaid device-to-device communications: Performance and tradeoffs. IEEE Transaction on Wireless Communications, 2016, 15 (6): 3949-3963 doi: 10.1109/TWC.2016.2531652
                      [5] Han Z, Swindlehurst A L, Liu K. Optimization of MANET connectivity via smart deployment/movement of unmanned air vehicles. IEEE Transaction on Vehicular Technology, 2009, 58 (7): 3533-3546 doi: 10.1109/TVT.2009.2015953
                      [6] Mozaffari M, Saad W, Bennis M, et al. Optimal transport theory for power-efficient deployment of unmanned aerial vehicles. In: Proceeding of the 2016 IEEE International Conference on Communications (ICC). Piscataway, USA: IEEE, 2016. 1-6
                      [7] Pang Y, Zhang Y, Gu Y, et al. Efficient data collection for wireless rechargeable sensor clusters in harsh terrains using UAVs. In: Proceeding of the 2016 IEEE Global Communications Conference (GLOBECOM). Piscataway, USA: IEEE, 2014. 234-239
                      [8] Abuzainab N, Saad W, Poor H V. Cognitive hierarchy theory for heterogeneous uplink multiple access in the internet of things. In: Proceeding of the 2016 IEEE International Symposium on Information Theory (ISIT). Piscataway, USA: IEEE, 2016. 1252-1256
                      [9] Tu C Y, Ho C Y, Huang C Y. Energy-efficient algorithms and evaluations for massive access management in cellular based machine to machine communications. In: Proceeding of the 2011 IEEE Vehicular Technology Conference (VTC). Piscataway, USA: IEEE, 2011. 1-5
                      [10] Daniel K, Wietfeld C. Using public network infrastructures for UAV remote sensing in civilian security operations. Tech. Rep., 2011
                      [11] Rohde S, Wietfeld C. Interference aware positioning of aerial relays for cell overload and outage compensation. In: Proceeding of the 2012 IEEE Vehicular Technology Conference (VTC). Piscataway, USA: IEEE, 2012. 1-5
                      [12] Jiang F, Swindlehurst A L. Optimization of UAV heading for the ground-to-air uplink. IEEE Journal on Selected Areas in Communications, 2012, 30 (5): 993-1005 doi: 10.1109/JSAC.2012.120614
                      [13] Shalmashi S, Bjornson E, Kountouris M, et al. Energy efficiency and sum rate tradeoffs for massive MIMO systems with underlaid device-to-device communications. EURASIP Journal on Wireless Communications and Networking, 2016, 2016 (1): 175 doi: 10.1186/s13638-016-0678-1
                      [14] Lin X, Heath R, Andrews J. The interplay between massive MIMO and underlaid D2D networking. IEEE Transaction on Wireless Communications, 2015, 14 (6): 1-10 doi: 10.1109/TWC.2015.2434891
                      [15] 白天翔, 王帥, 沈震, 等. 平行機器人與平行無人系統: 框架、結構、過程、平臺及其應用. 自動化學報, 2017, 43 (2): 161-175 doi: 10.16383/j.aas.2017.y000002

                      Bai Tian-Xiang, Wang Shuai, Shen Zhen, et al. Parallel robotics and parallel unmanned systems: Framework, structure, process, platform and applications. Acta Automatica Sinica, 2017, 43 (2): 161-175 doi: 10.16383/j.aas.2017.y000002
                      [16] 胡向東, 王瑞, 胡蓉. 一種改進的物聯網感知層簇維護優化算法. 系統工程與電子技術, 2017, 39 (1): 198-205 https://www.cnki.com.cn/Article/CJFDTOTAL-XTYD201701031.htm

                      Hu Xiang-Dong, Wang Rui, Hu Rong. Improved optimization algorithm of clusters maintenance for sensing layer of the internet of things. Systems Engineering and Electronics, 2017, 39 (1): 198-205 https://www.cnki.com.cn/Article/CJFDTOTAL-XTYD201701031.htm
                      [17] 陳珍萍, 黃友銳, 唐超禮, 等. 物聯網感知層低能耗時間同步方法研究. 電子學報, 2017, 44 (1): 193-199 https://www.cnki.com.cn/Article/CJFDTOTAL-DZXU201601028.htm

                      Chen Zhen-Ping, Huang You-Rui, Tang Chao-Li, et al. Research on low energy consumption time synchronization method for internet of things' perception layer. Acta Electronica Sinica, 2016, 44 (1): 193-199 https://www.cnki.com.cn/Article/CJFDTOTAL-DZXU201601028.htm
                      [18] Hourani A, Kandeepan S, Jamalipour A. Modeling air-to-ground path loss for low altitude platforms in urban environments. In: Proceeding of the 2014 IEEE Global Communications Conference (GLOBECOM). Piscataway, USA: IEEE, 2014. 2898-2904
                      [19] Fei Z, Li B, Yang S, et al. A survey of multi-objective optimization in wireless sensor networks: metrics, algorithms and open problems. IEEE Communications Surveys & Tutorials, 2017, 19: 550-586 http://ieeexplore.ieee.org/document/7570253
                      [20] 張霞, 周剛, 于宏毅. 一種協作和中繼混合的傳感網壽命最大化路由算法. 軟件學報, 2013, 24 (12): 2859-2870 https://www.cnki.com.cn/Article/CJFDTOTAL-RJXB201312007.htm

                      Zhang Xia, Zhou Gang, Yu Hong-Yi. Cooperative and forwarding hybrid routing algorithm for network lifetime maximization in wireless sensor network. Journal of Software, 2013, 24 (12): 2859-2870 https://www.cnki.com.cn/Article/CJFDTOTAL-RJXB201312007.htm
                      [21] 侯定仁. 內點算法研究[碩士論文], 中國科學技術大學, 中國2001

                      Hou Ding-Ren. Research on Interior-point Algorithm[Master thesis], University of Science and Technology of China, China 2001
                      [22] 劉美杏. 不等式約束優化新型SQCQP算法研究[碩士論文], 廣西大學, 中國2014

                      Liu Mei-Xing. Research on New SQCQP Algorithms for Inequality Constrained Optimization[Master thesis], Guangxi University, China 2014
                    • 加載中
                    圖(11) / 表(4)
                    計量
                    • 文章訪問數:  39
                    • HTML全文瀏覽量:  18
                    • PDF下載量:  12
                    • 被引次數: 0
                    出版歷程
                    • 收稿日期:  2018-03-14
                    • 錄用日期:  2018-08-17
                    • 刊出日期:  2021-08-20

                    目錄

                      /

                      返回文章
                      返回