Target tracking in wireless sensor network usually schedules a subset of sensor nodes to constitute a tasking cluster to collaboratively track a target.For the goals of saving energy consumption,prolonging network lif...Target tracking in wireless sensor network usually schedules a subset of sensor nodes to constitute a tasking cluster to collaboratively track a target.For the goals of saving energy consumption,prolonging network lifetime and improving tracking accuracy,sensor node scheduling for target tracking is indeed a multi-objective optimization problem.In this paper,a multi-objective optimization sensor node scheduling algorithm is proposed.It employs the unscented Kalman filtering algorithm for target state estimation and establishes tracking accuracy index,predicts the energy consumption of candidate sensor nodes,analyzes the relationship between network lifetime and remaining energy balance so as to construct energy efficiency index.Simulation results show that,compared with the existing sensor node scheduling,our proposed algorithm can achieve superior tracking accuracy and energy efficiency.展开更多
As a novel dynamic network service infrastructure, Internet of Things （IoT） has gained remarkable popularity with obvious su- periorities in the interoperability and real-time communication. Despite of the convenien...As a novel dynamic network service infrastructure, Internet of Things （IoT） has gained remarkable popularity with obvious su- periorities in the interoperability and real-time communication. Despite of the convenience in collecting information to provide the decision basis for the users, the vulnerability of embed- ded sensor nodes in multimedia devices makes the malware propagation a growing serious problem, which would harm the security of devices and their users financially and physi- cally in wireless multimedia system （WMS）. Therefore, many researches related to the mal- ware propagation and suppression have been proposed to protect the topology and system security of wireless multimedia network. In these studies, the epidemic model is of great significance to the analysis of malware prop- agation. Considering the cloud and state tran- sition of sensor nodes, a cloud-assisted model for malware detection and the dynamic differ- ential game against malware propagation are proposed in this paper. Firstly, a SVM based malware detection model is constructed with the data sharing at the security platform in the cloud. Then the number of malware-infected nodes with physical infectivity to susceptible nodes is calculated precisely based on the at- tributes of WMS transmission. Then the statetransition among WMS the modified epidemic devices is defined by model. Furthermore, a dynamic differential game and target cost function are successively derived for the Nash equilibrium between malware and WMS sys- tem. On this basis, a saddle-point malware de- tection and suppression algorithm is presented depending on the modified epidemic model and the computation of optimal strategies. Nu- merical results and comparisons show that the proposed algorithm can increase the utility of WMS efficiently and effectively.展开更多
To satisfy the needs of modem pre-cision agriculture, a Precision Agriculture Sensing System （PASS） is designed, which is based on wireless multimedia sensor network. Both hardware and software of PASS are tai-lored...To satisfy the needs of modem pre-cision agriculture, a Precision Agriculture Sensing System （PASS） is designed, which is based on wireless multimedia sensor network. Both hardware and software of PASS are tai-lored for sensing in wide farmland without human supervision. A dedicated single-chip sensor node platform is designed specially for wireless multi-media sensor network. To guarantee the bulky data transmission, a bit-map index reliable data transmission mecha-nism is proposed. And a battery-array switch-ing system is design to power the sensor node to elongate the lifetime. The effectiveness and performance of PASS have been evaluated through comprehensive experiments and large-scale real-life deployment.展开更多
基金Supported by the National Natural Science Foundation of China(No.90820302,60805027)the Research Fund for Doctoral Program of Higher Education(No.200805330005)the Academician Foundation of Hunan(No.2009FJ4030)
文摘Target tracking in wireless sensor network usually schedules a subset of sensor nodes to constitute a tasking cluster to collaboratively track a target.For the goals of saving energy consumption,prolonging network lifetime and improving tracking accuracy,sensor node scheduling for target tracking is indeed a multi-objective optimization problem.In this paper,a multi-objective optimization sensor node scheduling algorithm is proposed.It employs the unscented Kalman filtering algorithm for target state estimation and establishes tracking accuracy index,predicts the energy consumption of candidate sensor nodes,analyzes the relationship between network lifetime and remaining energy balance so as to construct energy efficiency index.Simulation results show that,compared with the existing sensor node scheduling,our proposed algorithm can achieve superior tracking accuracy and energy efficiency.
基金supported by the National Science Key Lab Fund under Grant No. KJ-15-104the Project of Henan Provincial Key Scientific and Technological Research under Grant No. 132102210003
文摘As a novel dynamic network service infrastructure, Internet of Things （IoT） has gained remarkable popularity with obvious su- periorities in the interoperability and real-time communication. Despite of the convenience in collecting information to provide the decision basis for the users, the vulnerability of embed- ded sensor nodes in multimedia devices makes the malware propagation a growing serious problem, which would harm the security of devices and their users financially and physi- cally in wireless multimedia system （WMS）. Therefore, many researches related to the mal- ware propagation and suppression have been proposed to protect the topology and system security of wireless multimedia network. In these studies, the epidemic model is of great significance to the analysis of malware prop- agation. Considering the cloud and state tran- sition of sensor nodes, a cloud-assisted model for malware detection and the dynamic differ- ential game against malware propagation are proposed in this paper. Firstly, a SVM based malware detection model is constructed with the data sharing at the security platform in the cloud. Then the number of malware-infected nodes with physical infectivity to susceptible nodes is calculated precisely based on the at- tributes of WMS transmission. Then the statetransition among WMS the modified epidemic devices is defined by model. Furthermore, a dynamic differential game and target cost function are successively derived for the Nash equilibrium between malware and WMS sys- tem. On this basis, a saddle-point malware de- tection and suppression algorithm is presented depending on the modified epidemic model and the computation of optimal strategies. Nu- merical results and comparisons show that the proposed algorithm can increase the utility of WMS efficiently and effectively.
基金supported in part by the Special Scientific Research Funds for Commonweal Section under Grant No. 200903010the Science and Technology Project of Jiangxi Province under Grants No. 20112BBF60050, No. 20121BBF60058
文摘To satisfy the needs of modem pre-cision agriculture, a Precision Agriculture Sensing System （PASS） is designed, which is based on wireless multimedia sensor network. Both hardware and software of PASS are tai-lored for sensing in wide farmland without human supervision. A dedicated single-chip sensor node platform is designed specially for wireless multi-media sensor network. To guarantee the bulky data transmission, a bit-map index reliable data transmission mecha-nism is proposed. And a battery-array switch-ing system is design to power the sensor node to elongate the lifetime. The effectiveness and performance of PASS have been evaluated through comprehensive experiments and large-scale real-life deployment.
