在感測網路(sensor network)中，受限於感測節點(sensor node)的能量有限與不可充電性，如何節省感測節點(sensor node)能源是我們要探討的一項重要課題。在LEACH演算法中，利用叢集法(clustering method)將系統切割成數個叢集，由叢集頭(cluster head)將蒐集來的資料做整合(aggregation)之後，然後傳送至遠端的基地台(base station)，且全部的感測節點以隨機的方式輪流擔任叢集群首，這樣的方法可以平均分配能源的負擔於所有的感測節點。
對LEACH而言，叢集頭的選擇方式有著不穩定以及無法平均分配感測空間的問題。在本篇論文中，我們提出改良式叢集頭選擇法(Improved Cluster-Head selection)，針對佈署完感測節點後的空間進行改良，使叢集頭能夠在高密度的叢集節點中被選出，來達到多數叢集成員(Cluster member)皆在被選出叢集頭的傳送範圍。最後用模擬的方式來證實改善部份與LEACH演算法在穩態相位(Steady-state phase)之間的改善部份，顯示出改良式叢集頭選擇法可延長整體感測節點網路的生命週期。

In sensor network, we focus on the energy-saving issues by the limited power and un-chargeable battery. In LEACH algorithm, the operation runs a model to divide the system into many clusters which has one cluster-head. The cluster-head nodes collect information transmitted from the cluster-members and do some process and relay the data to the base station far beyond.
In LEACH algorithm, the cluster-head selection model has some drawbacks such as unstable number of cluster-head and unevenly distributed cluster-head. In this paper, we propose an improved cluster-head selection for the phase after the deployment to select the cluster-head in higher density, so that the cluster members are almost in the cluster-head’s transmission range. Finally, the simulation results shows the improvement between the method and the LEACH algorithm in the steady-state phase that extend the lifetime of the system.

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