浅谈移动代理网络中速度的利用

J. Beauquier, J. Burman, J. Clément, S. Kutten
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引用次数: 31

摘要

人口协议是最近提出的一个模型,用于具有非常大的,可能未知数量的具有小内存的移动代理的网络。对于这种网络,这种模型比其他模型(如DTN)具有一定的优势。然而,研究表明,该模型的计算能力仅限于半线性谓词。因此,提出了各种扩展。我们提出了一个模型,通过引入agent速度的(弱)概念来增强种群协议的原始模型。这种增强使我们能够仅用弱需求设计快速收敛协议(例如,假设有不同类型的代理,比如附着在生病动物和健康动物上的代理,两个相遇代理只需要能够估计哪一个更快,例如,使用它们的类型,但实际上不知道它们类型的速度)。然后,使用新模型,我们研究了收集问题,其中存在未知数量的匿名代理,这些代理具有应该传递给基站的值(没有复制)。我们逐步开发高效的协议,寻找最优解决方案并适应可用内存的大小。这些协议很简单,但它们的分析有些复杂。我们还给出了一个更复杂的结果——任何协议的最差执行长度的下界。我们的证明引入了几种技术,这些技术在未来的人口协议时间研究中也可能被证明是有用的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On utilizing speed in networks of mobile agents
Population protocols are a model presented recently for networks with a very large, possibly unknown number of mobile agents having small memory. This model has certain advantages over alternative models (such as DTN) for such networks. However, it was shown that the computational power of this model is limited to semi-linear predicates only. Hence, various extensions were suggested. We present a model that enhances the original model of population protocols by introducing a (weak) notion of speed of the agents. This enhancement allows us to design fast converging protocols with only weak requirements (for example, suppose that there are different types of agents, say agents attached to sick animals and to healthy animals, two meeting agents just need to be able to estimate which of them is faster, e.g., using their types, but not to actually know the speeds of their types). Then, using the new model, we study the gathering problem, in which there is an unknown number of anonymous agents that have values they should deliver to a base station (without replications). We develop efficient protocols step by step searching for an optimal solution and adapting to the size of the available memory. The protocols are simple, though their analysis is somewhat involved. We also present a more involved result - a lower bound on the length of the worst execution for any protocol. Our proofs introduce several techniques that may prove useful also in future studies of time in population protocols.
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