In the process of Wireless Sensor Network(WSN) node positioning,it is more important to improve the x-axis and y-axis positioning accuracy of an unknown node than z-axis positioning accuracy,so this paper proposes a positioning algorithm based on planar projection on the basis of RSSI Gaussian Mixed(RGM) algorithm.It improves unknown node positioning accuracy on the x-axis and y-axis directions by reducing the projected area of spatial positioning error region.Simulation results show that,compared with RGM algorithm,the proposed algorithm can improve the x-axis and y-axis positioning accuracy without any inscrease in time complexity and network traffic.

Aiming at the problem of high overhead and unbalanced energy consumption caused by exchanging majority of messages for higher accuracy in typical algorithms,an energy-balanced and low-overhead time synchronization algorithm for wireless sensor networks is proposed.Based on a hierarchical topology,cluster heads accomplish the process by pair-wise message exchange mechanism with the Sink node,and adopt maximum likelihood estimation for the clock offset and skew correction,thus improving precision and decreasing the times of the synchronization process.Considing broadcasting properties and remaining energy,cluster members synchronizes to their cluster head by adopting pair-wise packet exchange and reference broadcast mechanism,thus reducing numbers of transmission packets and balancing the energy in the network.Simulation results show that the proposed algorithm relatively has less packet cost,balances the energy consumption and extends the network lifetion.while guaranteeing the precision.

Aiming at the problem that the traditional three-dimensional localization algorithm for sensor network nodes produce a singular matrix and high complexity,an improved localization algorithm based on three-edge measurement is proposed to realize node localization for Wireless Sensor Network(WSN),which is suitable for 3D localization in wireless sensor networks.The proposed algorithm obtains offset vector volume by tetrahedron formula.The target location of the 2D Linear Least Squares Estimation(LLSE) transformation is applied on the plane vector rotation.The target location is calculated by target position and offset vector.Simulation results show that compared with the traditional 3D Levenberg Marquardt (LM) localization algorithm,the proposed algorithm improves the accuracy by about 10% and not singular matrix,and the complexity is lower.

Intelligent meter reading system based on Wireless Sensor Network(WSN) can improve efficiency,but it has higher power consumption.Therefore,its nodes need to work under listen-sleep mode to reduce the power consumption.For this working mode,a rapid node wake-up method for WSN is proposed for hand-held meter reading and the system is designed.With the proposed method,higher communication rate is improved between handsets and sensor nodes.As a result,the average current in sensor nodes can be reduced significantly.Performance analysis result shows that the proposed method can reduce the average current.Furthermore,the proposed method yields obvious advantage in saving power consumption when the listen-sleep period is short.Hence,the proposed method is suitable for hand-held meter reading,which generally requires short responding time from sensor nodes.

The cluster head nodes selected by Low Energy Adaptive Clustering Hierarchy(LEACH)protocol suffer from imbalance ofdistribution and energy consumption.In view of these problems,this paper proposes an improved LEACH algorithm based on Rough C-means(RCM) clustering.Firstly,using location technology,it gets the position coordinates of the nodes,and then the nodes’ locations of Wireless Sensor Network(WSN)are clustered by the RCM clustering algorithm,which can guarantee uniform distribution of cluster heads in the location.Secondly,considering the residual energy of nodes,it selects cluster head nodes by the LEACH algorithm.Calculation results show that,when choosing cluster head nodes in each round,the improved algorithm can guarantee the cluster head nodes be evenly distributed in the network,and prolongs the network life cycle.

In order to exchange information of partial likelihood function in a distributed target tracking,several common distributed target tracking methods are studied,and a Distributed Particle Filter method based on Belief Propagation(DPF-BP) is proposed.The maximum diameter of the graph is calculated in a limited number of iterations.In order to avoid difference in network assessment,consistency maximization is used before assessing and nodes and the number of iterations are expressed as a function.After standardization and valuation calculations,the replacement is re-sampled.Simulation experimental results show that,compared with Standard Belief Consensus(SBC),Randomized Gossip(RG)and Metropolis Belief Consensus(MBC),under the condition of the same configuration,DPF-BP is excellent at RootMean Square Error(RMSE).In addition,DPF-MBC is best in the circular network,and DPF-BP is best in the tree network.

When events distribute nonuniformly in the wireless sensor monitoring network,hot spots will appear in data-centric storage algorithms.Aiming at this problem,this paper introduces storage thresholds and event priorities,considers nodes’ remaining memory when selecting storage nodes,and proposes a new snake-like slot time data storage algorithm.It determines the distance from event storage location to query node grid according to the event priority,to reduce node’s energy consumption in process of data storage and query.Defining a node storage threshold,nodes reaching the threshold are no longer involved in the next round of time slot allocation.When all nodes in a grid reach the storage threshold,it stores data into neighbor grids with the same priority level.When all nodes in all grids of the same priority reach one storage threshold,it reallocates work slot,which effectively reduces the nonuniform distribution.Simulation results show that the proposed algorithm has better performance than the Snake-like Slot Time Power-saving Data Stroage Algorithm based on Event Priority(P-SLPS) in residual energy of nodes and the network life cycle.

In order to improve the survival period of wireless sensor networks,a data collection protocol for Wireless Sensor Network(WSN) based on dichotomy and mobile Sink called PBDM is proposed.The network is divided into two equal subdomains by the dichotomy,the intersection of two domains is the trajectory of mobile Sink.With the increase of mortality rate of sensors,and the inner subdomain is divided into two equal areas by the dichotomy,which can identify and change the trajectory of the mobile Sink.The entire network is controlled by topology,where static and mobile Sink nodes coexist.Cluster heads collect interests in the cluster and send the data to the nearest Sink with minimum hop counts.Simulation results show that PBDM is better than LEACH in the base station to obtain information,the remaining energy of the network and the number of surviving nodes.It can improve the efficiency of data collection and prolong the lifetime of WSN.

Network data fusion and cluster are effective technologies to reduce energy consumption of Wireless Sensor Network(WSN),however,clustering produces extra delays in the process of data aggregation,and the problem can be solved by the modified network structure. A Delay-aware Network Structure for WSNs with Data Fusion(DANSDF)is proposed. The proposed structure organizes sensor nodes into clusters of different sizes,each cluster can communicate with the fusion center in an interleaved manner. Simulation results show that compared with Low Energy Adaptive Clustering Hierarchy(LEACH),Delay-aware Data Collection Network Structure(DADCNS) the two network structures,DANSDF can reduce the delay in the process of data fusion,and can keep a low energy consumption.

Target localization and tracking technology is currently a hot issue in Wireless Sensor Network(WSN). Conventional target tracking algorithms always require an explicit system observation model of the target positions, which,however,would fail if such model is not available. This paper designs a distributed algorithm for the localization and pursuit of multiple mobile targets using mobile robot. By the proposed algorithm,all robots are categorized into two groups:the leaders,responsible for the target pursuit,and the followers,responsible for the formation and connectivity maintenance,and then the relation between convergence error and system parameter setting is analyzed theoretically. Simulation results show that the proposed target pursuit algorithm is proved to be able to achieve a controllable convergence error to the local maximum points,which depends on the moving speed and sampling rate of agents.

In the existing directional sensor networks,the centroid point of node model mostly rotates around the sector vertex. As in this model,the node rotation area is a full circle,and therefore multiplies the network energy consumption and deployment time. For coverage optimization problem of Wireless Sensor Network(WSN) in complex area,this paper uses the new directional model which the sector nodes rotate around the centroid in the previous work,then presents a coverage optimizing algorithm in complex area based on virtual potential field (COACA) to implement deployment optimization by reducing the node’s rotation area. Finally,it makes simulation for this algorithm to explore the parameters which will affect the coverage ratio and contrast with PFPCE algorithm. The simulation results show the high performance of the COACA algorithm in both coverage radio and time efficiency.

Aiming at the presence that obstacles exist in the monitored area,introducing a kind of obstacle avoidance strategy,this paper puts forward a PCMOD(Potential field based Coverage optimization algorithm to multi-obstacle scene for directional sensor networks). The algorithm is based on the directional sensing model,by means of overlapping coverage area,the effective coverage and virtual force of interaction between obstacles block area,adjusts node sensing direction and gradually eliminates the network of overlapping coverage and blind area, and improves the boundary condition by adding a neighbor node in the boundary line,makes sensor network coverage enhancement. On this basis,it analyzes the impact of sensor parameters on coverage rate. Simulation results show that the proposed algorithm can improve coverage rate in obstacle situation.

Traditional area location algorithms based on midnormal have low positioning accuracy and number of iterations. Aiming at these problems,an Improved Midnormal-based area Localization Algorithm(IMBLA) is proposed in this paper. According to the value ratio of Received Signal Strength Indicator ( RSSI ) of two anchor nodes which unknown node receives,it moves two midnormals of the anchor,to determine the position relationship between a node and the midnormal. The algorithm does the RSSI raging using Gaussian correction model based on the reference anchor node, and puts forward the model in the presence of obstacles,which not only is suitable for a variety of environment,but also can effectively prevent malicious attacks. The simulation results show that,compared with MBLA and IPAIT algorithm, the IMBLA algorithm has higher positioning accuracy and coverage rate.