用塞纳河分析自私泛滥

Guido Lena Cota, Sonia Ben Mokhtar, G. Gianini, E. Damiani, J. Lawall, Gilles Muller, L. Brunie
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引用次数: 5

摘要

自私是协作式分布式系统(例如,文件共享网络,自愿计算)的开发者所面临的关键问题之一。它有可能严重降低系统性能,导致不稳定和故障。目前用于理解自私行为的影响和设计有效对策的技术仍然是手工和耗时的,需要多领域的专业知识。为了克服这些困难,我们提出了SEINE,一个用于快速建模和评估合作系统中自私行为的仿真框架。SEINE依赖于特定于领域的语言(SEINE- l)来指定自私场景,并在最先进的模拟器中为其实现和研究提供半自动支持。我们在本文中表明:(1)SEINE- l具有足够的表现力,可以指定从文献中提取的15种自私场景;(2)与真实实验相比,SEINE在预测自私的影响方面是准确的;(3)与传统的人工方法相比,SEINE大大减少了开发工作量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysing Selfishness Flooding with SEINE
Selfishness is one of the key problems that confronts developers of cooperative distributed systems (e.g., file-sharing networks, voluntary computing). It has the potential to severely degrade system performance and to lead to instability and failures. Current techniques for understanding the impact of selfish behaviours and designing effective countermeasures remain manual and time-consuming, requiring multi-domain expertise. To overcome these difficulties, we propose SEINE, a simulation framework for rapid modelling and evaluation of selfish behaviours in a cooperative system. SEINE relies on a domain-specific language (SEINE-L) for specifying selfishness scenarios, and provides semi-automatic support for their implementation and study in a state-of-the-art simulator. We show in this paper that (1) SEINE-L is expressive enough to specify fifteen selfishness scenarios taken from the literature, (2) SEINE is accurate in predicting the impact of selfishness compared to real experiments, and (3) SEINE substantially reduces the development effort compared to traditional manual approaches.
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