视觉传感器网络边界部署k-覆盖数量估计
|
摘要
覆盖是评价视觉传感器网络对感兴趣区域(Field of Interest,FoI)监测质量的重要指标.与传统的全向传感器节点不同,视觉传感器节点的感知区域为扇形区域,其覆盖估计问题也更加复杂.目前,大量视觉传感器网络的研究工作主要假设同构节点随机部署在感兴趣区域内以对其实现覆盖.该文假设所有节点随机部署在感兴趣区域的外部边界以对FoI实现覆盖监测,同时研究异构部署的k-覆盖率估计问题.针对此应用场景,该文首次提出k-覆盖率估计模型,通过仿真对场景k-覆盖率,仿真值及模型理论值进行比较分析,结果表明模型理论值与场景仿真值的平均绝对覆盖误差基本保持在6%以内.该文的研究对边界部署的视觉传感器网络具有重要的指导意义.
Recently,Visual Sensor Networks(VSNs)consist of a great number of visual sensors have attracted a lot of attention due to its wide range of applications in different fields of environment monitoring,traffic surveillance,country security etc.Coverage problem is an important metric for evaluating the monitoring quality of field of view(FoI)in visual sensor networks.Besides,coverage estimation is one of the fundamental issues in the fields of coverage problem of visual sensor networks.Different from traditional omnidirectional sensors networks,coverage estimation problem in visual sensor networks is more complicated and challenging due to the sensing region of visual sensor is a sector region and the sensing direction is adjustable.At present,the majority of existing literatures mainly assume that a large number of homogeneous visual sensors are directly deployed in the FoI.However,in some actual application scenarios,such as channel water monitoring,country security etc,consider that the FoI is inaccessible or difficult to deploy sensors directly,visual sensors cannot be directly scattered in the FoI,and only be deployed outside of the FoI.In this paper,we assume that all visual sensors are randomly scattered in the boundary area of the FoI,and study the k-coverage estimation problem of homogeneous or heterogeneous deployment of visual sensor networks,simultaneously.To address the k-coverage estimation in such application scenario,firstly,we propose the concepts of effective possiblesensing region and its mathematical expectation which represents the average sensing contribution of visual sensors located in the boundary area to the FoI,and then we make analysis of the mathematical expectation of effective possible sensing region from two actual situations.Secondly,based on the related definitions and concepts of k-coverage estimation problem in visual sensor networks,when a large number of visual sensors are randomly scattered in a region R with densityλ,we prove that the probability of a subregion in which containing k visual sensors is satisfied with Poisson distribution from two aspects of probability theory and simulation analysis.By using of the Poisson distribution,we propose a k-coverage model of homogeneous or heterogeneous visual sensor networks,which reflects the mathematical relationship between node density,sensing radius,field of view,width of boundary area,width of FoI and k-coverage ratio,to estimate the minimum number of visual sensors needed to achieve a certain level of coverage.Finally,in order to evaluate the performance of the proposed model,a series of simulation experiments are carried out to verify the theoretical results.We mainly analyze the simulation experiments from two aspects:the influence of parameters of the FoI and the influence of parameters of the visual sensor.The results show that the Mean Absolute Coverage Difference(MACD)between the theoretical values and the experimental values is basically controlled less than 6%.The proposed model has a good performance of guiding actual deployment of visual sensor networks in such application scenario we studied.At the same time,the research of this paper has important guiding significance for the visual sensor networks based on boundary deployment.
Recently,Visual Sensor Networks(VSNs)consist of a great number of visual sensors have attracted a lot of attention due to its wide range of applications in different fields of environment monitoring,traffic surveillance,country security etc.Coverage problem is an important metric for evaluating the monitoring quality of field of view(FoI)in visual sensor networks.Besides,coverage estimation is one of the fundamental issues in the fields of coverage problem of visual sensor networks.Different from traditional omnidirectional sensors networks,coverage estimation problem in visual sensor networks is more complicated and challenging due to the sensing region of visual sensor is a sector region and the sensing direction is adjustable.At present,the majority of existing literatures mainly assume that a large number of homogeneous visual sensors are directly deployed in the FoI.However,in some actual application scenarios,such as channel water monitoring,country security etc,consider that the FoI is inaccessible or difficult to deploy sensors directly,visual sensors cannot be directly scattered in the FoI,and only be deployed outside of the FoI.In this paper,we assume that all visual sensors are randomly scattered in the boundary area of the FoI,and study the k-coverage estimation problem of homogeneous or heterogeneous deployment of visual sensor networks,simultaneously.To address the k-coverage estimation in such application scenario,firstly,we propose the concepts of effective possiblesensing region and its mathematical expectation which represents the average sensing contribution of visual sensors located in the boundary area to the FoI,and then we make analysis of the mathematical expectation of effective possible sensing region from two actual situations.Secondly,based on the related definitions and concepts of k-coverage estimation problem in visual sensor networks,when a large number of visual sensors are randomly scattered in a region R with densityλ,we prove that the probability of a subregion in which containing k visual sensors is satisfied with Poisson distribution from two aspects of probability theory and simulation analysis.By using of the Poisson distribution,we propose a k-coverage model of homogeneous or heterogeneous visual sensor networks,which reflects the mathematical relationship between node density,sensing radius,field of view,width of boundary area,width of FoI and k-coverage ratio,to estimate the minimum number of visual sensors needed to achieve a certain level of coverage.Finally,in order to evaluate the performance of the proposed model,a series of simulation experiments are carried out to verify the theoretical results.We mainly analyze the simulation experiments from two aspects:the influence of parameters of the FoI and the influence of parameters of the visual sensor.The results show that the Mean Absolute Coverage Difference(MACD)between the theoretical values and the experimental values is basically controlled less than 6%.The proposed model has a good performance of guiding actual deployment of visual sensor networks in such application scenario we studied.At the same time,the research of this paper has important guiding significance for the visual sensor networks based on boundary deployment.
引文
[1]Ma Hua-Dong,Tao Dan.Multimedia sensor network and its research progresses.Journal of Software,2006,17(9):2013-2028(in Chinese)(马华东,陶丹.多媒体传感器网络及其研究进展.软件学报,2006,17(9):2013-2028)
[2]Brass P.Bounds on coverage and target detection capabilities for models of networks of mobile sensors.ACM Transactions on Sensor Networks,2007,3(2):9
[3]Yen L-H,Yu C-W,Cheng Y-M.Expected k-coverage in wireless sensor networks.Ad Hoc Networks,2006,4(5):636-650
[4]Li J-S,Kao H-C.Distributed k-coverage self-location estimation scheme based on voronoi diagram.IET Communications,2010,4(2):167-177
[5]Xing Xiao-Fei,Wang Guo-Jun,Li Jie.A square-based coverage and connectivity probability model for WSNs.International Journal of Sensor Networks,2015,19(3/4):161-170
[6]Ling Q,Tian Z.Minimum node degree and k-connectivity of wireless multihop network in bounded area//Proceedings of the IEEE Global Telecommunications Conference.Washington,USA,2007:1296-1301
[7]Gupta H-P,Rao S-V,Tamarapalli V.Analysis of stochastic k-coverage and connectivity in sensor networks with boundary deployment.IEEE Transactions on Intelligent Transportation Systems,2015,16(4):1861-1871
[8]Zhao Jing,Zeng Jian-Chao.Sense model and number estimation of wireless multimedia sensor networks.Journal of Software,2012,23(8):2104-2114(in Chinese)(赵静,曾建潮.无线多媒体传感器网络感知模型与数量估计.软件学报,2012,23(8):2104-2114)
[9]Liu Zhi-Min,Jia Wei-Jia,Wang Guo-Jun.Coverage prediction model and number estimation for directional sensor networks.Journal of Software,2016,27(12):3120-3130(in Chinese)(刘志敏,贾维嘉,王国军.有向传感器网络覆盖预测与数量估计.软件学报,2016,27(12):3120-3130)
[10]Karakaya M,Qi H.Coverage estimation in heterogeneous visual sensor networks//Proceedings of the IEEE International Conference on Distributed Computing in Sensor Systems,Hangzhou,China,2012:41-49
[11]Zhao D,Ma H-D,Liu L.Analysis for heterogeneous coverage problem in multimedia sensor networks//Proceedings of the IEEE International Conference on Communications.Kyoto,Japan,2011:1-5
[12]Wang Yi,Gao Guo-Hong.Achieving full-view coverage in camera sensor networks.ACM Transactions on Sensor Networks,2013,10(1):1-31
[13]He Shi-Bo,Shin D-H,Zhang Jun-Shan,et al.Full-view area coverage in camera sensor networks:Dimension reduction and near-optimal solutions.IEEE Transactions on Vehicular Technology,2016,65(9):1-14
[14]Yu Zuo-Ming,Yang Fan,Teng Jin,et al.Local face-view barrier coverage in camera sensor networks.Computer Communications,2015:684-692
[15]Lin Ting-Yu,Santoso H,Wu Kun-Ru,et al.Enhanced deployment algorithms for heterogeneous directional mobile sensors in a bounded monitoring area.IEEE Transactions on Mobile Computing,2017,16(3):744-758
[16]Hu Y,Wang X,Gan X.Critical sensing range for mobile heterogeneous camera sensor networks//Proceedings of the IEEE Conference on Computer Communications.Toronto,Canada,2014:970-978
(1)Surface water.http://www.ysi.com/
(2)Railway track.http://metrom-rail.com/
(3)Country border.http://www.ultra-ccs.com/details/4
[2]Brass P.Bounds on coverage and target detection capabilities for models of networks of mobile sensors.ACM Transactions on Sensor Networks,2007,3(2):9
[3]Yen L-H,Yu C-W,Cheng Y-M.Expected k-coverage in wireless sensor networks.Ad Hoc Networks,2006,4(5):636-650
[4]Li J-S,Kao H-C.Distributed k-coverage self-location estimation scheme based on voronoi diagram.IET Communications,2010,4(2):167-177
[5]Xing Xiao-Fei,Wang Guo-Jun,Li Jie.A square-based coverage and connectivity probability model for WSNs.International Journal of Sensor Networks,2015,19(3/4):161-170
[6]Ling Q,Tian Z.Minimum node degree and k-connectivity of wireless multihop network in bounded area//Proceedings of the IEEE Global Telecommunications Conference.Washington,USA,2007:1296-1301
[7]Gupta H-P,Rao S-V,Tamarapalli V.Analysis of stochastic k-coverage and connectivity in sensor networks with boundary deployment.IEEE Transactions on Intelligent Transportation Systems,2015,16(4):1861-1871
[8]Zhao Jing,Zeng Jian-Chao.Sense model and number estimation of wireless multimedia sensor networks.Journal of Software,2012,23(8):2104-2114(in Chinese)(赵静,曾建潮.无线多媒体传感器网络感知模型与数量估计.软件学报,2012,23(8):2104-2114)
[9]Liu Zhi-Min,Jia Wei-Jia,Wang Guo-Jun.Coverage prediction model and number estimation for directional sensor networks.Journal of Software,2016,27(12):3120-3130(in Chinese)(刘志敏,贾维嘉,王国军.有向传感器网络覆盖预测与数量估计.软件学报,2016,27(12):3120-3130)
[10]Karakaya M,Qi H.Coverage estimation in heterogeneous visual sensor networks//Proceedings of the IEEE International Conference on Distributed Computing in Sensor Systems,Hangzhou,China,2012:41-49
[11]Zhao D,Ma H-D,Liu L.Analysis for heterogeneous coverage problem in multimedia sensor networks//Proceedings of the IEEE International Conference on Communications.Kyoto,Japan,2011:1-5
[12]Wang Yi,Gao Guo-Hong.Achieving full-view coverage in camera sensor networks.ACM Transactions on Sensor Networks,2013,10(1):1-31
[13]He Shi-Bo,Shin D-H,Zhang Jun-Shan,et al.Full-view area coverage in camera sensor networks:Dimension reduction and near-optimal solutions.IEEE Transactions on Vehicular Technology,2016,65(9):1-14
[14]Yu Zuo-Ming,Yang Fan,Teng Jin,et al.Local face-view barrier coverage in camera sensor networks.Computer Communications,2015:684-692
[15]Lin Ting-Yu,Santoso H,Wu Kun-Ru,et al.Enhanced deployment algorithms for heterogeneous directional mobile sensors in a bounded monitoring area.IEEE Transactions on Mobile Computing,2017,16(3):744-758
[16]Hu Y,Wang X,Gan X.Critical sensing range for mobile heterogeneous camera sensor networks//Proceedings of the IEEE Conference on Computer Communications.Toronto,Canada,2014:970-978
(1)Surface water.http://www.ysi.com/
(2)Railway track.http://metrom-rail.com/
(3)Country border.http://www.ultra-ccs.com/details/4