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The coverability of Wireless Sensor Networks (WSNs) is essentially a Quality of Service (QoS) problem that measures how well the monitored area is covered by one or more sensor nodes.The coverability of WSNs was examined by combining existing computational geometry techniques such as the Voronoi diagram and Delaunay triangulation with graph theoretical algorithmic techniques.Three new evaluation algorithms,known as CRM (Comprehensive Risk Minimization),TWS (Threshold Weight Shortest path),and CSM (Comprehensive Support Maximization),were introduced to better measure the coverability.The experimental results show that the CRM and CSM algorithms perform better than the MAM (MAximize Minimum weight) and MIM (MInimize Maximum weight) algorithms,respectively.In addition,the TWS algorithm can provide a lower bound detection possibility that accurately reflects the coverability of the wireless sensor nodes.Both theoretical and experimental analyses show that the proposed CRM,TWS,and CSM algorithms have O(n 2) complexity.
The coverability of Wireless Sensor Networks (WSNs) is essentially a Quality of Service (QoS) problem that measures how well the monitored area is covered by one or more sensor nodes. The coverability of WSNs was examined by combining existing computational geometry techniques such as the Voronoi diagram and Delaunay triangulation with graph theory algorithmic techniques. Novel evaluation algorithms, known as CRM (Comprehensive Risk Minimization), TWS (Threshold Weight Shortest path), and CSM (Comprehensive Support Maximization), were introduced to better measure the coverability. experimental results show that the CRM and CSM algorithms perform better than the MAM (MAximize Minimum weight) and MIM (MInimize Maximum weight) algorithms, respectively. In addition, the TWS algorithm can provide a lower bound detection possibility that accurately reflects the coverability of the wireless sensor nodes.Both theoretical and experimental analyzes show that the proposed CRM, TWS, and CSM algor ithms have O (n 2) complexity.