Study On The Robustness Of Wireless Sensor Networks Based On The Cloud Model

Robustness means that the structure of the system and the performance is still able to maintain the basic stability of the capacity when the various parameters change occurs. Because of the wireless deployment and long-term monitoring, the wireless sensor network is the first choice to lots of users, especially industrial network. Unlike the field of commercial office, there is a high demand in real-time signal transmission and transmission reliability in industrial production. Therefore, it is necessary to put forward a evaluation method for network robust performance testing and analysis. The same time, the overall performance of the wireless sensor network can be acquired after analysis and evaluation. And then it is easy for the users to assess and accept an existing network. The robustness is an important performance indicators for the wireless sensor network and the the basic properties of complex systems. So the conclusion of the scientific evaluation indicators, which is established by the combination methods in theoretical analysis and simulation model, not only help to weigh the degrees of the pros and cons in different systems, and also provide the valuable reference for the formation as well as the application of wireless sensor system.Cloud model combines the fuzziness and randomness preferably of things in the universe and the human knowledge. The cloud model made it possible that the quantitative data and the distribution law can be acqured from the qualitative information of the language expression, and the precise values can be changed into the certain qualitative linguistic values effectively.The cloud model is introduced to the assessment of the robustness performance of the wireless sensor network after being discussed about the characteristics in dealing with the uncertainty. Then the robust performance evaluation model based on cloud model of wireless sensor networks was put forward. The cloud model is introduced to solve the uncertainty, randomness and fuzziness. For a more comprehensive introduction of cloud model, this calculation process is divided into two directions, one is from the qualitative representation to the quantitative description, and then to the qualitative representation, the other one is from the quantitative description to the qualitative representation, and then to the quantitative description. The proposed model in the article did not use the membership function and solve the problem that it is difficult for the traditional comprehensive evaluation to determine the membership function. In order to avoid the influence of subjective factors on the results, the entropy weight was used to conform the weight, which reduced the influences by the subjective factors, after contrasting different methods in determining the weight. Secondly, the paper put forward a robustness performance assessment research method of wireless sensor networks robust based on multi-dimensional cloud model. First, change the original data after processing into a matrix. Second, transform matrix for vector. Third, calculate the measure of the degree of similarity by the cosine of the angle. Finally, determine the index level, where the cloud model used reasonable. Experiments show that the method that is the cloud model is applied to the problem of the robustness performance evaluation of wireless sensor networks is advancement, effective and there is theoretical significance and value in use.The results of this study were preliminary attempt on the robust performance applications based on the cloud model in wireless sensor networks, a meaningful exploration of the cloud model used in robust performance applications and wireless sensor networks, and also provides an effective new ideas for the cloud model in wireless sensor network technology applications.