Energy-Balance Routing Protocol And Node Localization Algorithm For Wireless Sensor Network

Routing and localization are important components of Wireless Sensor Networks, energy efficiency is an important limiting factor of WSN architecture, geographical posi-tion information reflects the system’s application significance. Research work begins from node localization, hierarchical clustering algorithm, geographic routing, data fusion in nodes, optimal transmission path, path recovery and Skyline query in data acquisi-tion.The dissertation mainly contains the following contents:Firstly, the dissertation presents Environment Aware Hybrid Localization Algorithm (EAHLA) to solve the problem of nodes location known earlier in DSE-GAF & NACO. Localization error is due to unstable RSSI affected by environment. An environment aware for algorithm is achieved by beacon location and RSSI applied to offset effect of signal attenuation. Offline confidence fingerprint positioning database is created associa-ted with the path loss index. If RSSI filtered can satisfy confidence constraint, nodes position is solved with centroid algorithm after finding nearest K neighbors in fingerprint positioning database with K-NNSS. Otherwise, received RSSI is dealed with Gaussian model, distance between the unkown node and beacons is calculated via maximum communication distance and corrected with distance scaling relation, the least square method is used to solve the maximum likelihood solution of the unknown node position, and the weighted coefficients are designed to realize the node’s centroid localization. The factors affecting algorithm accurancy are analyzed, and effectiveness is verified in experiment and simulation.Secondly, the dissertation presents the algorithm of distribution equilibrium, similar data and Energy-balance GAF(DES-GAF). After analysising influence fators on performan-ce of geographical adaptive fidelity(GAF), DES-GAF adopts regular haxgan like honeycomb to cover WSN area, defines distribution equilibrium model and gives a method for solving the optimal radius of the virtual cell. Cluster-head election process considers residual energy and the parameter difined as cluster-head selection evaluation based on distribution equilibrium model, and similar data theory is given as the basis of data fusion in WSN transimission. Simulation results show that energy efficiency is emproved, energy consumption is balanced, and the network life cycle is prolonged at different distribution equilibrium.Thirdly, the dissertation presents a new ACO-based routing optimization & path recovery algorithm (NACO) for WSN. In order to solve the problem of optimal path to Sink and avoid detours phenomenon, the improved heuristic function is consisited of residual energy, distance between nodes communication and transmission direction. When failure node appears in the opitmal path, a path recovery strategy is adopted that selected neighbor node takes over failure node, inherits pheromones from failure node and links up the interrupt path. So most of the original optimal path is retained and search for optimal again is avoided. Simulation results show that energy efficiency is enhanced, energy consumption is balanced better, and quick path recover is effective.Finally, the location-oriented MR-EDBNL(Ext-Dominate-BNL based on MapReduce) algorithm is proposed. In order to query extreme value of physical quantities around monitoring in a period of time, Skyline query on related dimensions (such as time, node location, types of monitoring) is needed in mass data acquisition of WSN. Correlation definition and theorem about Ext-dominate are raised to weaken domination from strong to weak, filter a large number of non Skyline data objects around the monitoring with location, and downsize the initial data. The defined ext-dominate capacity are used to sort and delete non Skyline date in Reduce process, it avoids a great deal of unnecessary comparison operation. MR-EDBNL is implemented to verify the effectiveness in experiment.