我們介紹一種以P2P 網路為基礎的主題式發佈/訂閱系統，如何能更有效的利用網路的資源，分散負載於更多的節點上，有效的利用分散式網路。
透過分析Attribute的出現機率，將之分類為熱門(Hot)與非熱門(Cold)兩大類，然後再針對各種情況，我們提出幾種有效的策略來分散負載於更多的節點上。
我們提出的方法可以在變動event數量、subscription數量、attribute數量、與網路大小的情況下表現出高適應度。而且我們也與許多不同的發佈/訂閱系統做比較來證明這些結果。

We propose a new content-based publish/subscribe system, called Fleet, that decouples subscription storage and event delivery mechanisms and seamlessly combines a novel subscription mapping scheme and an address space partitioning technique to derive an effective publish/subscribe system over a distributed hash table (DHT) overlay. To combat skewed attribute distributions in subscriptions and events, we propose a number of novel strategies that exploit of the popularity of attributes to spread the load across a multitude of peers. Fleet strikes an ideal balance between subscription storage cost and event delivery cost, and is shown to be scalable in the number of events, subscriptions, schema attributes, and network peers. Using an extensive set of experiments, Fleet is compared to other state of the art systems and is shown to be superior.

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