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Hybrid Optimization For Dynamic Deployment Algorithm Based On Yukawa Potential In Wireless Sensor Networks

Posted on:2019-02-24Degree:MasterType:Thesis
Country:ChinaCandidate:Z W LiuFull Text:PDF
GTID:2348330542977716Subject:Computer Science and Technology
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Wireless sensor network(WSN)is one of the key research topics in the world,which involves the frontier communications,remote sensing,electronics and other related fields.With the development of information technology,wireless sensor technology is gradually mature.It becomes cheaper and more efficient to manufacture different kinds of sensor nodes and use them in different industries.WSN has been widely used in lots of applications,which has been extended from the original military field to other areas,such as traffic control,environmental monitoring,security system,national defense,space observation and internet of things et al.WSN has very important value both in scientific research and real applications.In the WSN applications,the random node deployment will easily lead to the problem of uneven distribution and affect the connectivity and coverage of whole network.For the large-scale WSN,how to efficiently implement the dynamic deployment of all sensor nodes and form an effective cellular coverage is a key method to solve this problem.The optimized algorithm based on virtual force or virtual potential field have already become one of hot research issues in node deployment of WSN.In this paper,we firstly focus on the theory based on Yukawa potential model in dusty plasma simulations and give a novel virtual force algorithm in WSN applications.In order to discuss the effect of this algorithm,we bring the Delaunay triangulation into the Yukawa potential model to improve the adjustment of computation scale which can achieve the actual requirements in WSN applications.Our simulation results verify the effectiveness of this algorithm based on Yukawa potential.Furhermore,the effect of computation scale and shielding length are detailedly discussed and analyzed.For a fixed shield length,when computation scale increases,the system uniformity becomes better and the network topology is more close to the perfect hexagonal topology.However,the runtime also increases.For a fixed computation scale,when shield length increases,the coverage area becomes larger,but the system uniformity becomes worse and the network topology is poor.Simulations indicate that this algorithm can form a good hexagonal topology with fast convergence,especially in a large-scale WSN application.Moreover,we use this virtual force algorithm based on Yukawa potential(VFA_YP)as a fundamental method.Then,We combine it with another virtual force algorithm based on the exchange force(VFA_LJ)between sensor nodes and present a hybrid optimization of node deployment strategy.The VFA_YP has better system coverage and uniformity,but needs more time to reach the equilibrium state and costs more energy consumption.The VFA_LJ only calculates the direct force from the closest adjacent nodes of a given sensor.It is a rapid deployment and can effectively shorten the deployment time and reduce the energy consumption of the system.But it may cause poor uniformity and coverage holes.According to the characteristics of these two algorithms,we firstly use VFA_YP to form a large-scale hexagonal system topology,and then use VFA_LJ to adjust the deployment of adjacent nodes for each sensor to perform a better self-consistent hybrid optimization.Simulation results show that this strategy has faster convergence speed,better network uniformity,higher coverage rate and better network topology in steady state(more close to the perfect hexagonal topology).In the application of wireless sensor network,using optimized virtual force algorithm and hybrid deployment strategy in this paper can shorten the node deployment time,have a higher coverage of the monitoring area,enhance the robustness and fault-tolerant rate of network.
Keywords/Search Tags:Wireless Sensor Networks, Virtual Force, Delaunay Triangulation, Yukawa Potential, Hybrid Optimization
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