Mesh Wireless Network Node Platform Design And Development

Wireless mesh network is not existed for a long time; this techque attracts people's attention mostly in the mid 20 century. The appearance of wireless mesh network is not accidental but develops by direct requirement of clients, just like other new techs. The main contributions are listed as follows:1. In a wireless mesh network (WMN), the traffic is aggregated and forwarded towards the gateways. Strategically placing and connecting the gateways to the wired backbone is critical to the management and efficient operation of a WMN. In this paper, we address the problem of gateways placement in multi-task and multi-channel wireless mesh networks, consisting in placing a minimum number of gateways such that quality-of-service (QoS) requirements are satisfied. We propose a polynomial time near-optimal algorithm which recursively computes maximal users Dominating Sets (DS), while consistently preserving QoS requirements before iterations. We evaluate the performance of our algorithm using both analysis and simulation.2. Up to date, most blind source separation algorithms need sufficient pre-condition, that is, the number of observed signals should be more or at least equivalent to the number of source signals. This paper develop a new algorithm which can try its best to separate the mixed signals under the condition of below, the only needed condition is mixed matrix should be row full rank. Further we transform to solve a generalized eigenvector which corresponding eigenvalue is the ratio of the covariance of a part sum of observed signals and the covariance of observed signals, the convergence speed is very fast. The algorithm shows its efficiency for signals separation with ill-mixed signals. The computer simulation shows its outstanding performance on blind source separation approach.3. This paper develops a new framework which used to different emotion recognition and reconstruction base on wireless mesh networks architecture. Because of constrained capacity of wireless transmission, we propose a solution which projects the different emotional vectors to base space which generate by ICA algorithm; we make the face recognition happen through projection. This paper firstly develops a framework to recognize different emotion base on ICA (Independent Component Analysis) algorithm. Because PCA (Principle Component Analysis) is lack of detailed description in removing eyeglasses from frontal facial image, so we develop a new framework to reconstruct the different emotion with eyeglasses on frontal facial image, and then synthesizes a natural looking eyeglasses facial image by recursive error compensation. The synthesized images have no trace of the eyeglasses or the reflection and shade caused by the eyeglasses. Test results show that the method can effectively synthesize eyeglasses. The recognition rate increases up to 70%.