CAJ | 학술논문

提出一种应用于大规模环境监测领域无线传感器网络（WSN）中改进的基于压缩感知（CS）数据收集方案。该方案改进联合稀疏模型（JSM）进行数据分析；并采用分簇路由采集并传输数据，即每簇簇内使用基于CS的数据收集方法，簇头之间采用最短路径路由到达汇聚节点。仿真结果表明，该方案不仅缩小了数据处理的分布范围，降低了恢复误差，而且大大减少了数据传输次数，维持了整个网络的能耗平衡。
제출일충응용우대규모배경감측영역무선전감기망락（WSN）중개진적기우압축감지（CS）수거수집방안。해방안개진연합희소모형（JSM）진행수거분석；병채용분족로유채집병전수수거，즉매족족내사용기우CS적수거수집방법，족두지간채용최단로경로유도체회취절점。방진결과표명，해방안불부축소료수거처리적분포범위，강저료회복오차，이차대대감소료수거전수차수，유지료정개망락적능모평형。
A scheme of an improved data gathering based on compressed sensing(CS)in wireless sensor networks(WSN) for large-scale environmental monitoring is proposed in this paper. The approximate joint sparsity model(JSM)is modified to analyze data. The clustering routing is adopted to perform the data acquisition and transmission,that is to say,CS-based data gathering method is used within each cluster,and the shortest path routing is adopted between the cluster heads to reach the sink node. The simulation results show that the approach not only shrinks the distribution range of data processing and reduces the recovery error,but also greatly lessens the number of data transmission and maintains energy balance of the entire network.