基於 IEEE 802.11 的無線區域網路 (Wireless Lacal Area Network, WLAN)已被廣泛
應用於日常生活之中，而無線基地台 (Access Point, AP)的負載量會影響無線區域網路
的效能，因此需要一種機制來控制無線基地台之間的負載量，用以提昇整體網路效能
與可靠度。本文提出以多重搜尋多重起點為架構，微型基因演算法為基礎的複合式演
算法，用來運算一個固定範圍內所有使用者與所有無線基地台之間最佳的連線狀態。
最終的實驗結果顯示，我們提出的方法可綜合原始基因演算法與微型基因演算法的優
點，提昇解的品質但是保有計算時間上的優勢。

Wireless local area network (WLAN) based on IEEE 802.11 standards has been widely
used for mobile devices to access the Internet today; however, the load of access point (AP)
may significantly impact the performance of a WLAN. That is why an effective mechanism
is needed to balance the load of APs—so as to avoid the congestion problem of WLANs—to
maximize the performance of all the clients. To improve the performance, and the scalability,
of WLANs, a modified multiple-search multi-start framework for the micro-genetic algorithm
(micro-GA) to decide the connection state of each client is presented in this thesis. Simulation
results show that the proposed algorithm outperforms GA and micro-GA in terms of both the
computation time and the quality

論文審定書 i
誌謝 iii
摘要 iv
Abstract v
List of Figures viii
List of Tables x
Chapter 1 簡介 1
1.1 動機 2
1.2 論文貢獻 3
1.3 論文架構 3
Chapter 2 相關文獻探討 4
2.1 無線區域網路負載平衡 4
2.2 基因演算法與無線區域網路負載平衡的應用 7
2.3 結論 10
Chapter 3 改良式多重起點之多重搜尋架構應用於微型基因演算法 11
3.1 問題定義 11
3.2 演算法流程 13
3.2.1 多重起點之多重搜尋架構 14
3.2.2 改良式多重起點之多重搜尋架構應用於微型基因演算法 15
3.2.3 結論 16
3.3 範例 17
Chapter 4 實驗結果 19
4.1 執行環境、參數設定 19
4.2 數據分析 20
4.2.1 實驗資料 20
4.2.2 結果與時間分析 20
4.2.3 負載平衡分析 22
4.2.4 參數分析 23
4.2.4.1 候選池使用率測試及分析 24
4.2.4.2 解集合數量測試及分析 24
4.2.4.3 收斂參數測試及分析 27
4.2.5 原始 MSMS 與改良式 MSMS 應用於微型基因演算法測試與實驗分析 28
4.2.5.1 實驗資料 28
4.2.5.2 原始 MSMS 與改良 MSMS 版本介紹 28
4.3 總結 32
Chapter 5 結論與未來展望 33
5.1 結論 33
5.2 未來展望 33
Bibliography 35

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