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.
Flash-based Solid State Drive ( SSD ) can improve the performance of On-line Transaction Processing (OLTP) database efficiently. Due to the high cost of SSD products,however,SSD is usually utilized in hybrid storage combined with traditional disks. Therefore,this paper proposes an adaptive data layout optimization algorithm and two specific strategies. The algorithm can adjust the characteristic of application adaptively,through observing and deciding the performance improvement efficiency of each data element,to form an optimized data layout between SSD and disks. Experimental results based on a practical database system show that the algorithm is flexible and efficient to adapt to various SSD capacity configurations,and can improve the performance of the OLTP database based on hybrid storage effectively.