在同儕環境下，快速判斷一個候補資料提供者是否有足夠的能力來提供服務，對於使用者是有很多好處的。目前現有的相關研究，著重於如何量測某候補資料提供者當下的剩餘服務能力。然而，服務能力的變化趨勢比當下的量測值更為重要。所以，本研究採取了一個新奇的預測方式來選出資料提供者。我們所採用的做法是，根據客戶端過去的服務狀況與當下的負載狀況，來估算它未來提供良好服務的機率。根據預測結果，客戶端可以互相調配以平衡負載。另外，我們僅對網路延遲小的候補資料提供者進行預測，以提高找到合適提供者的機率。初步的模擬資料顯示，在網路頻寬多變的環境下，我們的預測方法有很高的準確度，而且僅造成少許時間延遲以及訊息流量。

Peer-to-peer applications require an accurate technique to identify the high-performance peers which can provide a requested bandwidth. Existing approaches resort to measurements of network paths to determine the current available bandwidth for a given connection, but ignore the past bandwidth situation. In this paper, we propose a novel approach that considers the past service quality and the current workload of a peer to predict the probability of a requested bandwidth being available in the near future. Combined with the information of network latencies, close peers with high predicted probabilities will be chosen to be the data providers. Our preliminary simulation results show the high accuracy and efficiency of our prediction approach.

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