在無線感測網路中為了滿足指定的感測工作，覆蓋問題是個很典型的問題。一般而言，感測覆蓋代表著一個區域能被感測器監測得多好的程度。在本篇論文中，我們提出一個有效利用電量的覆蓋保存協定同時能夠維持整個感測區域充分地被覆蓋。在我們提出的協定中，我們嘗試找出最小工作的節點集合以達到最節省電量的目的，我們將他模組化為一個最小集合覆蓋的問題並以一種貪婪的演算法去解決它。另外，我們延伸基本的協定令其能滿足多重覆蓋問題和機率覆蓋問題，機率覆蓋問題是能實際反應在感測網路中真實的應用，基於機率偵測模型，在監控區域中的任意點在任何時間內至少要被一個節點所感測在一個由應用所指定的信賴機率下。模擬結果顯示我們提出的協定比起之前文獻確實能達到較好的效能和顯著地減少電量的耗費。另外，模擬結果也顯示，在給定的信賴機率下，我們可以執行我們的機率覆蓋保存協定並尋找出最佳答案來解決機率覆蓋問題。 Coverage is a typical problem in wireless sensor networks to fulfill the issued sensing tasks. In general, sensing coverage represents how well an area is monitored by sensors. In this thesis, we propose an energy-efficient coverage preserving protocol while maintaining the sensing field sufficiently covered. In our proposed protocol, we try to select minimal active set of sensor nodes to reach mostly energy conservation while maintain the complete area coverage. We model it as a minimum-set-cover problem and solve it by a heuristic greedy algorithm. Besides, we extend our basic protocol to satisfy k-coverage requirement and probabilistic coverage problem which is more realistic to reflect physical applications of sensor networks. Based on the probabilistic sensor detection model, any point anytime in the monitoring region is sensed by at least one node is no lower than a confidence probability which is specified by the applications. Simulation results have shown that our proposed protocols achieve better performance and decrease the energy expenditure noticeably than the previous works. Moreover, Simulation result has also demonstrated that we can execute our coverage preserving protocol to find out the best solution to solve the probabilistic coverage problem when the confidence probability is given.
