結論與未來展望方向

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第六章、 結論與未來展望方向

大型天然災害發生時通訊系統常會癱瘓，而有效運作的通訊系統卻是災情傳 遞、資源調度以及互助協調是否順利的關鍵因素。我們提出利用無線電將功能完 整但無法對外進行正常連線的基地台連接起來，建構一個臨時性的行動通訊網路，

稱為應急蜂巢式行動通訊網路(Contingency Cellular Network，CCN)，由於各個地 方受災情況不盡相同且通訊資源有限，CCN 必須反應災區需求之輕重緩急妥適 分配頻寬，因此在網路拓樸規劃完成，基地台依排程陸續開通服務後，必須根據 各地災情緊急程度及網路拓樸進行 CCN 頻寬分配規劃，以達到最大的救災效 益。

本研究提出一個兼顧各基地台災情緊急程度以及通訊需求差異，且適合於 CCN 樹狀結構的最佳化頻寬分配模型，以追求救災效益的最大化。這些模型可 供使用者(救災指揮單位)系統化的解決 CCN 頻寬分配問題。頻寬分配給基地台 可獲得之效益由救災單位根據所收集到的各地災情自行定義，本模型及頻寬分配 演算法可決定 CCN 連外頻寬使用之分配。

CCN 頻寬分配問題是 Nested 0-1 Knapsack Problem，我們證明該問題屬於 NP-Hard 問題，但因為發生突發性大型天然災害時，可容許之計算時間極為短暫，

因此我們提出一個啟發式演算法：BAG，以快速得到一個相近於最佳解的頻寬 分配。BAG 演算法透過 Profit density 找出每次頻寬分配的最佳 Profit 配置，並在 確認頻寬資源後配發，直到剩餘的 CCN 連外頻寬無法再配發任何一種 Channel 使用為止。因此在限定時間內即可提供不錯的頻寬分配組合，並且每當網路拓樸、

可用頻寬或災情程度變動時，能快速的重新運算修改頻寬分配。

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我們利用電腦模擬評估演算法之效能，假設網路拓樸及頻寬資源固定，以 基地台個數多寡來分析其對演算法的影響，實驗一、二分別以不同之效益遞減函 數帶入。實驗案例由亂數隨機產生，以正規化的誤差值來評估頻寬分配組合之優 劣。結果顯示，我們提出之演算法可在數秒內得出與最佳解誤差範圍在 0~14.03%

之近似最佳解。

本研究提出的模型仍有改進之空間，例如加入 CCN 各鄰台間剩餘的頻寬運 用考量、以節點為單位作為頻寬分配效益遞減範圍、網路拓樸變化對演算法效能 及誤差之影響與改良、非單一路由選擇之頻寬分配、反應環境變化之動態頻寬分 配、配合允入控制的調適。此外，如能聯合不同電信公司之基地台建構 CCN 時，

CCN 的連外可能不再是單一出口，且各地區可供應急通訊用的基地台也不再是 單一選擇，而必須在服務範圍相互重疊的數個基地台內擇一加入，如何於多重路 由與多重連外資源整體考量下妥適分配頻寬亦是研究課題，避免資源分配之重疊，

浪費寶貴的災區通訊資源。

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