Modeling and understanding BitTorrent (BT) dynamics is a recurrent research topic mainly due to its high complexity and tremendous practical efficiency. Over the years, different models have uncovered various phenomena exhibited by the system, many of which have direct impact on its performance. In this paper we identify and characterize a phenomenon that has not been previously observed: homogeneous peers (with respect to their upload capacities) experience heterogeneous download times. This behavior has direct impact on peer and system performance, such as high variability of download times, unfairness with respect to peer arrival order, bursty departures and content synchronization. Detailed packet-level simulations and prototype-based experiments on the Internet were performed to characterize this phenomenon. We also develop a mathematical model that accurately predicts the heterogeneous download rates of the homogeneous peers as a function of their content. In addition, we apply the model to calculate lower and upper bounds to the number of departures that occur in a burst. The heterogeneous download rates are more prevalent in unpopular swarms (very few peers). Although few works have addressed this kind of swarm, these by far represent the most common type of swarm in BT.
翻译:建模和理解 BitTorrent (BT) 动态是一个经常性的研究课题,主要因为其复杂程度高、实际效率高。多年来,不同的模型揭示了系统展示的各种现象,其中许多现象直接影响到该系统的性能。在本文中,我们确定并描述一个以前没有观察到的现象:同质同行(在上传能力方面)经历不同的下载时间。这种行为对同行和系统性能产生直接影响,例如下载时间变化很大、同龄人抵达顺序不公、暴动和内容同步。在互联网上进行了详细的包级模拟和原型实验,以说明这一现象的特点。我们还开发了一个数学模型,准确预测同质同行的异性下载率是其内容的函数。此外,我们用该模型来计算暴发中发生的离差次数的下限和上限数。在非流行的群群群群(很少同龄人)中,混杂的下载率比较普遍。尽管很少有研究针对这种群群,但远代表BT最常见的群。