Optimal data collection of MR-MC wireless sensors network for structural monitoring applications
Structural health monitoring(SHM)is a kind of data-intensive applications for wireless sensors networks,which usually requires high network bandwidth.However,the bandwidth of traditional single-radio single-channel(SR-SC)WSN is quite limited.In order to meet the requirement of structural monitoring,multi-radio multi-channel(MR-MC)WSN is emerging.In this paper,we address the optimal data collection problem in MR-MC WSN by modelling it as an integer linear programming problem.The particle swarm optimization(PSO)has many benefits,such as greater convergence,resolving optimization efficiently,and directing an early converging towards a local optima via the search velocity,and the flower pollination optimization(FPA)algorithm has good exploration characteristics via Levy flight.Combining the advantages of the PSO algorithm and FPA,we propose a new hybrid algorithm BFPAPSO to solve the optimization problem under the constraint of time slot and multi-power multi-radio multi-channel(MP-MR-MC).For reflecting the physical reality more precisely,we adopt physical interference model and take node residual energy into account.Furthermore,we use the data receiving rate at the sink in one round to measure its achievable network capacity.One of the most important steps for solving MP-MR-MC problem concerns the link extraction,target at finding the most important subset of links that leads to the best fitness,i.e.achieving optimal network capacity and total energy consumption,we use the Major Link Strategy(MLS)to construct a routing tree,in which data can be transmitted concurrently without interference.The experiments results show that the network capacity improvement and energy consumption decrease in SHM can be achieved by utilizing MPMR-MC communication.Compared to BPSO,BBA,GA,BGSA,BFPA,BFPA-PSO has obvious advantages in convergence and global optimization.The general principle of BFPAPSO is shown in Figure 1.
Structural health monitoring data collection MR-MC BFPA-PSO
Q.Li Z.Chen L.Wu
College of Physics and Information Engineering,Fuzhou University,Fuzhou,China
国际会议
The 7th World Conference on Structural Control and Monitoring(7WCSCM)(第七届结构控制与监测世界大会)
青岛
英文
2756-2757
2018-07-22（万方平台首次上网日期，不代表论文的发表时间）