Research On Localization Techniques Based On Convex Programming In Wireless Sensor And Actuator Networks

Wireless Sensor and Actuator Network (WSAN) is a kind of new network derived from the traditional Wireless Sensor Network (WSN) and based on the introduction of actuators. Due to the introduction of actuators, WSAN expands the sensor networks in functionality and application areas tremendously, but it also faces many challenges, such as the coordination, communication and scheduling problem arising from heterogeneous nodes. In addition, to most of applications, it makes no sense for WSAN to gather sensor data without sensor location information. Thus, node localization is also the supporting technology to WSAN. At present, the localization technology about WSAN netwoks especially in the large-scale networks is still relatively limited. Consequently, research on the localization techniques in WSAN is conducted in the thesis on the basis of the related node localization investigation in WSN. Recent research about WSNs shows that convex programming localization techniques can provide better localization performance with less anchor nodes. Thus, learning from the ideas and methods of research inWSN, and combined WSAN own characteristics, the WSAN localization techniques based on convex programming are mainly studied in the thesis.First of all, on the basis of reading a lot of relevant information, this thesis describes the research status of the Wireless Sensor and Actuator Network at home and abroad, and classification of the wireless sensor network localization algorithm and nodes calculation method are presented. Meanwhile, some representative algorithms and achievement of research are mainly studied in the thesis.Secondly, second-order cone programming (SOCP), semi-definite programming and two kinds of SDP relaxation models including node-based SDP and edge-based SDP are presented. In these models, the localization problem is modeled as a convex optimization problem which takes the minimum distance error as the objective function, and the distance between nodes as the constraints, and then relaxed to an easy problem by related relaxation techniques. In addition, through theoretical analysis and simulation study, several range-based and range-free convex optimization localization methods are investigated in the thesis.Then, to several distributed localization models based on convex optimization, effectiveness and applicability of the various types of localization algorithms have been verified through the theoretical, mathematical formula analysis and simulation experiments. For the large-scale sensor network positioning, the gradient search algorithm is presented and applied to the cluster-based positioning, which effectively improves the performance of the cluster-based SDP distributed positioning algorithm. Sequential greedy optimization (SGO) algorithm is presented and applied to the ESDP positioning and its performance is significantly better than the distributed SOCP, and the refinement algorithm of SGO can further improve the positioning effect. The simulation results show that these localization models which are applied to the Wireless Sensor and Actuator Network have achieved effective results.Finally, the whole work of the research projects carried out is summarized in the thesis. And at last, the thesis points out the contents and recommendations for further research.