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BarterCast: A practical approach to prevent lazy freeriding in P2P networks

机译:BarterCast:一种防止P2P网络中的懒惰搭便车的实用方法

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A well-known problem in P2P systems is freeriding, where users do not share content if there is no incentive to do so. In this paper, we distinguish lazy freeriders that are merely reluctant to share but follow the protocol, versus die-hard freeriders that employ sophisticated methods to subvert the protocol. Existing incentive designs often provide theoretically attractive resistance against die-hard freeriding, yet are rarely deployed in real networks because of practical infeasibility. Meanwhile, real communities benefit greatly from prevention of lazy freeriding, but have only centralized technology available to do so. We present a lightweight, fully distributed mechanism called BARTERCAST that prevents lazy freeriding and is deployed in practice. BarterCast uses a maxflow reputation algorithm based on a peer's private history of its data exchanges as well as indirect information received from other peers. We assess different reputation policies under realistic, trace-based community conditions and show that our mechanism is consistent and effective, even when significant fractions of peers spread false information. Furthermore, we present results of the deployment of BarterCast in the BitTorrent-based Tribler network which currently has thousands of users worldwide.
机译:P2P系统中的一个众所周知的问题是搭便车,如果没有动力,用户不会共享内容。在本文中,我们区分了懒惰的免费骑行者,他们只是不愿意共享但遵循协议,而顽固的​​免费骑行者则采用复杂的方法来颠覆协议。现有的激励设计通常在理论上提供对顽固的搭便车的吸引力,但由于实际的不可行性而很少部署在实际网络中。同时,真实社区可以从防止懒惰搭便车中受益匪浅,但是只有集中式技术可以这样做。我们提出了一种称为BARTERCAST的轻量级,完全分布式的机制,该机制可防止懒惰搭便车并在实践中进行部署。 BarterCast使用基于对等方的数据交换的私有历史以及从其他对等方接收到的间接信息的maxflow信誉算法。我们在现实的,基于跟踪的社区条件下评估了不同的信誉政策,并表明我们的机制是一致且有效的,即使大部分同龄人散布了虚假信息。此外,我们介绍了在基于BitTorrent的Tribler网络中BarterCast部署的结果,该网络目前在全球拥有成千上万的用户。

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