A Study On Model Constraint Based Coverage-Enhancing Techniques In Wireless Sensor Networks

Coverage quality is one of the hot topics in the research field of wireless sensor networks. Dueto the different deployment environment of sensor networks, each node model has distinctivecharacteristics in the different applications. This dissertation mainly studies on coverageoptimization techni’ques for different nodes models, including directional sensing model,three-dimensional sensing model, directional sensing model based on the probability model andthree-dimensional underwater sensing model. This dissertation gives some solutions to improvecoverage optimization algorithms through the establishment of appropriate network models.Simulation results show that the improved algotirhm, compared to similar algorithms, has certainadvantages in saving energy and enhancing coverage rate. The main contents and contirbutions ofthis dissertation are as follows:(1)Itstudies on the judgment of sensory overlap region of two-dimensional sensing model. Thisdissertation redefines the directional sensing model. It analyzes and proves that the traditionaljudgment of sensory overlap region based on directional sensing model is not applicable, thenredefines the judgment using straddling pirnciple. It applies the new criteria to the virtual potentialifeld algorithm, and improves the calculation method of nod’es single moving angle. The simulationresults show that the improved algorithm, compared to the similar algorithms, has better coverageoptimization results and algorithm convergence.(2)Itimproves the coverage optimization algorithm for three-dimensional sensing model by usingcoveirng factor This dissertation points out that the traditional judgment of sensory overlap regionbased on3D directional sensing model is not applicable, and then redefines the judgment principles.Simulation results show that it could extend the lifetime of network using the new judgmentpirnciples. Secondly, it points out the defects about significant fluctuation of coverage rate andfrequent adjustment for nodes’ locations in current coverage optimization algorithms. For thesedefects, it improves the algorithm by using coveirng factor and centeral computing nodes.Simulation results show that the improved algotirhm has certain advantages in saving energy andenhancing coverage rate.(3)Itproposes the probability model based coverage-enhancing algorithm for wireless sensornetworks using nod’es adjustable movement pattern. Firstly the probability model is introduced intothe coverage-enhancing algorithm of the directional sensor network, and analyzes the influence of the probability model to the location of the centroid. Secondly, to the boundary coverage, throughthe simulations of typical algorithms which consider the boundary repulsion, it finds that thecoverage rates of the corners are much lower than the overall coverage. Adding a vertex force onthe corner is essential and to some extent would reduce the gap of coverage between them. Thirdly,it analyzes the drawbacks of single movement pattern of nodes. Finally, based on the randomdeployment of sensor nodes, a novel algorithm is proposed which determines whether the sensornode rotates or moves along fixed direction according to the coverage effect. A set of simulationexpeirments verify the performance of the proposed algorithm on coverage rate and networklifetime.(4)It studies on the underwater sensor networks based on redundancy model in the premise ofconsideirng boundary effects. In the study of three-dimensional underwater sensor networks, theperception ranges of nodes would be changed under the influence of environmental factors and theirown hardware. Requesting all nodes completely isomorphic is unrealistic. Ignoring boundaryeffects usually causes the coverage of the actual deployment of networks not to reach the expectedresult. Firstly it presents an underwater sensing model with normal distributed node sensing radius.Secondly, it gives the relationship between expected deployment quality and the number of nodes inth’e premise of consideirng boundary effects. Then, it deduces nodes redundancy formula based onthe sensing model with normal distributed node sensing radius, and this formula would determinewhether node itself a redundant node only based on the number of its neighbor nodes. Furthermore,it puts forward a redundancy model and virtual ifeld based coverage-enhancing algorithm (RVCT)for three-dimensional underwater sensor networks. Simulation results show that RVCT algorithm,compared to similar alglrithms, obtains teh satisfactory performance on saving energy andenhancing coverage rate.