At present, the deployment of nodes in wireless sensor network mainly adopts the algorithm based on Voronoi diagram. In the process of deployment using Voronoi algorithm, due to the large number of nodes involved in the deployment and the high complexity of the algorithm, the iteration time of the algorithm is long. In order to solve the problem of long iteration time in node deployment, a Deployment Algorithm based on Basic Architecture (DABA) was proposed. Firstly the nodes were combined into basic architectures, then center position coordinates of the basic architecture were calculated, finally the node deployment was performed by using Voronoi diagram. The algorithm was still able to realize the deployment effectively under the condition that there were obstacles in the deployment area. The experimental results show that DABA can reduce the deployment time by two thirds compared with the Voronoi algorithm. The proposed algorithm can significantly reduce the iteration time and the complexity of the algorithm.

Aiming at real-time requirements and elimination ghost produced by moving object in video stitching, a method based on circular Region Of Interest (ROI) image registration was proposed by using the simplified process and Graphics Processing Unit (GPU) acceleration. Firstly, the feature extraction only occured in the ROI area, which improved the detection speed and the feature matching accuracy. Secondly, to further reduce the time cost and meet the real-time requirements for video processing, two strategies were used. On one hand, only the first frame was used for matching, while the subsequent frames used the same homography matrix to blend. On the other hand, GPU was adopted to realize hardware acceleration. Besides, when there are dynamic objects in the field of view, the graph-cut and multi-band blending algorithms were used for image blending, which can effectively eliminate ghost image. When stitching two videos of 640×480, the processing speed of the proposed method was up to 27.8 frames per second. Compared with the Speeded Up Robust Features (SURF) and Oriented features from Accelerated Segment Test (FAST) and Rotated BRIEF (ORB), the efficiency of the proposed method was increased by 26.27 times and 11.57 times respectively. Experimental results show the proposed method can be used to stitch multi-channel videos into a high quality video.

To solve the sensor node localization problem of Wireless Sensor and Actor Network (WSAN), a range-based localization algorithm with virtual force in WSAN was proposed in this paper, in which mobile actor nodes were used instead of Wireless Sensor Network (WSN) anchors for localization algorithm, and Time Of Arrival (TOA) was combined with virtual force. In this algorithm, the actor nodes were driven under the action of virtual force and made themself move close to the sensor node which sent location request, and node localization was completed by the calculation of the distance between nodes according to the signal transmission time. The simulation results show that the localization success rate of the proposed algorithm can be improved by 20% and the average localization time and cost are less than the traditional TOA algorithm. It can apply to real-time field with small number of actor nodes.