由於無線感測網路是透過許多具有能量限制的微小節點裝置所組成的。這些感測器通常被佈置在人員較難到達的地方，因此，一但佈署好感測節點後通常不考慮回收與更換感測器的能量裝置。在這樣的條件限制下如何有效的使用有限的能量，並且在回傳感測資料時盡量降低能源的消耗來增進整個網路的運作時間與壽命，是大部分無線感測網路通訊協定設計時的最基本且重要考慮因素之一，其中一種典型的低能量適應性叢集式路由演算法(Low Energy Adaptive Clustering Hierarchy, LEACH)[4]即是考慮能源使用問題而設計的路由演算法。但由於LEACH演算法本身仍存在著一些缺陷與改善空間，因此後續有許多研究以此以演算法為基礎並加以改良，這些研究中有許多部分都著重在事先將感測網路中的節點劃分為群組，控制感測網路中叢集數量並改良叢集首的選擇方式。但這些改善方式中存在著能量消耗不平均的問題，導致某些節點死亡過快或是拖延過久。本文針對以事先將節點劃分為群組的方式，提出一個調整叢集規模改善負載平衡演算法(Improve Load-balance by Cluster Size Adjustment algorithm, ILCSA) 來改善網路負載平衡的問題，透過修改建立叢集時的規模大小來改善叢集之間規模大小不確定的問題，使網路中的感測節點能較平均的消耗能量來達到延長網路生命週期的目的，經由模擬結果顯示我們所提出的方法可以延後第一個感測節點死亡的時間，且從第一個節點死亡到最後一個節點死亡的經過時間也較短，表示網路中的能量消耗較為平均。

Since the wireless sensor network is composed of a number of tiny devices with energy constraints, each sensing node is limited in energy using. How the limited energy used effectively is a basic and important considered factor, and the design goal of most wireless sensing network protocols. Many researches control the number of clusters in the network by dividing the sensing nodes into groups in advance. However, there is still the problem of unbalanced energy consumption between clusters, resulting in shortened network life. In this thesis, we proposes a way to improve the energy utilization of the network nodes by adjusting the cluster size while considers the load-balancing factor of the network. The main idea is to adjust the cluster size based on the distance between the groups and the base stations. We use the software simulation to observe its performance, the simulation results show that energy consumption does tend to balance the trend, although its effect is still not ideal, but can determine the size of the cluster on the impact of network power consumption.

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