packet loss probability 中文意思是什麼

packet loss probability 解釋
分組損失概率
  • packet : n 1 包裹；小件行李；（郵件等的）一捆；小批；袋。2 （定期）郵船，班輪。3 〈英俚〉（打賭等中輸贏的...
  • loss : n. 1. 喪失；丟失，遺失。2. 減損，損失，虧損（額）；損耗；減少，下降。3. 失敗；輸掉。4. 錯過；浪費。5. 損毀；【軍事】傷亡；〈pl. 〉 傷亡及被俘人數。
  • probability : n 1 或有；或然性。2 【哲學】蓋然性〈在 certainly 和 doubt 或 posibility 之間〉。3 【數學】幾率，...
  1. By using fractional brownian motion envelope process and additional maximum delay constrain, the algorithm overcomes the shortcoming of those packet - loss - probability based methods which can not guarantee the packet maximum delay

    該演算法採用分形布朗運動包絡過程對自相似業務進行分析，通過增加最大延時約束條件，克服了原先基於分組丟失概率的有效帶寬計算方法不能保證業務最大延時要求的不足。
  2. The results indicate that the packet loss probability of spc is the limit of spl and spn

    結果表明: spc結構的丟包率是spl和spn結構丟包率的極限。
  3. Theory analyse indicate that the mdf algorithm can get the minimum packet loss probability that is same with faa, and meanwhile it can greatly reduce the number of lrwcs

    理論分析表明該演算法在達到faa最小丟包率的同時能夠更好的節約波長轉換器的數目。
  4. Simulations confirm compared with faa, the mdf can save more lrwcs and fewer packet loss probability, especially in the condition of high load. using mdf algorithm, the number of lrwcs in the condition of high load is more than in the condition of low load when the packet loss rate approaches to a fixed value

    通過模擬實驗驗證了該演算法在低、中和高負載情況下，比faa演算法更節約波長轉換器和更小的丟包率，而且在低負載時mdf演算法的優勢更加明顯。 mdf演算法在高負載下，丟包率到達穩定值所需要的lrwcs數目比低負載多。
  5. Aimed at the quality of service required by real - time service, an effective bandwidth calculating method for self - similar traffic is presented to provide guaranteed packet loss probability and maximum delay

    摘要針對多媒體實時業務需要提供特定服務質量的情況，給出了一種能夠同時保證分組丟失概率和最大延時的自相似業務等效帶寬計算方法。
  6. While the rate - based dropping on burst level large time scales determines the packet drop aggressiveness and is responsible for low and stable queuing delay, good robustness and responsiveness, the queue - based modulation of the packet drop probability on packet level small time scales will bring low loss and high throughput

    突發行為具有自相似或尺度不變性scale - invariant ，即流量在不同的時間尺度上具有相似的突發特性2局部縮放性。流量過程的局部奇異性使流量在小時間尺度數百ms及以下的突發非常強烈，具有非高斯分佈。
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