結論與未來工作

網路是 multi-hop 的環境，必須考量到 delay 可能變高且並無 association，因此本 論文基於 solicitation 的方式我們提出適應性聚集封包的機制，使可以在有限的 delay 下，end to end delay 降低且封包到達的成功率提升，並提高壓縮效益。

最後，我們透過 NS2 模擬軟體來模擬我們所提出的適應性聚集封包演算法，

我們可以透過上述 String-Topology 實驗結果看到在 traffic rate 為 0.2Mbps 傳輸 CBR 時平均 end to end delay 能降低 95%，封包到達率 hop 數小於 8 時能提高 87%~93%，hop 數大於 8 時因為能聚集的數量不多 queue drop 情況嚴重所以只能 提高 6%~9%，而在 traffic rate 為 64Kbps 傳輸 時平均 end to end delay 能降低 97%，封包到達率能提高 51%~85%。在 Freeway-Topology 實驗結果裡雖然能降 低平均 end to end delay 但由於車載網路的特性，車速慢且節點數多時使用適應性

7.2. 未來工作

本論文的實驗證明了使用標頭壓縮及適應性聚集封包的好處而因為目前採 用是 end to end 的壓縮聚集系統，中間節點只做 relay，在未來的工作裡，我們可 能可以在中間節點也做壓縮聚集，並在效能分析時，分析非固定的 hop delay，且 在模擬實驗的部份能加入我們的改良型 adaptive 程序包含 slow-start adaptive 程序 及 fast-recovery adaptive 程序並分析我們的策略在車載網路裡的效能影響，另外，

我們也可以傳輸 VBR 的 traffic type 並分析 throughput 或 utilization。

而本篇論文我們是將適應性聚集封包機制與 AODV 路由協定整合，我們也可 以嘗試將適應性聚集封包機制與不同的路由協定做整合，並互相比較其效能。

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